> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/v0.7/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server. # 0.7.0 ยท 26.10 ## Docs - [About NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/about.md): Overview of NeMo AutoModel, a PyTorch DTensor-native SPMD library with optimized model implementations and a Hugging Face-compatible API for training, fine-tuning, and as an accelerated backend for other frameworks - [Key Features and Concepts](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/key-features.md): Key features and core concepts of NeMo AutoModel for scalable LLM and VLM training with Hugging Face integration - [Install NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/installation.md): - [YAML Configuration](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/configuration.md): Configure NeMo AutoModel recipes with YAML, including target instantiation, distributed settings, prewarm options, and environment variable interpolation. - [Hugging Face Transformers API Compatibility](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/hf-compatibility.md): Summarizes Hugging Face Transformers API and artifact compatibility in NeMo AutoModel, including version support, drop-in APIs, and side-by-side examples. - [Repository Structure](https://docs.nvidia.com/nemo/automodel/v0.7/get-started/repo-structure.md): - [Announcements](https://docs.nvidia.com/nemo/automodel/v0.7/whats-new/announcements.md): - [Release Notes](https://docs.nvidia.com/nemo/automodel/v0.7/whats-new/release-notes.md): - [Model Support Log](https://docs.nvidia.com/nemo/automodel/v0.7/whats-new/model-release-log.md): A reverse-chronological log of model support added to NeMo AutoModel. - [Performance Summary](https://docs.nvidia.com/nemo/automodel/v0.7/performance/performance-summary.md): NeMo AutoModel training performance summary by GPU type and task, with benchmark recipes. - [Model Coverage Overview](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/overview.md): Hugging Face Auto class support, release history, day-0 coverage, and custom architecture registration for NeMo AutoModel. - [Model Support Log](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/release-log.md): A reverse-chronological log of model support added to NeMo AutoModel. - [Large Language Models (LLMs)](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/overview.md): - [Allen AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/allenai.md): Browse NeMo AutoModel coverage for Allen AI large language models. - [OLMo-1B-hf](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/allenai/OLMo-1B-hf.md): Reference OLMo-1B-hf checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [OLMo2-7B-1124](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/allenai/OLMo2-7B-1124.md): Reference OLMo2-7B-1124 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [OLMoE-1B-7B-0924](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/allenai/OLMoE-1B-7B-0924.md): Reference OLMoE-1B-7B-0924 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [BAAI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baai.md): Browse NeMo AutoModel coverage for BAAI large language models. - [Aquila-7B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baai/Aquila-7B.md): Reference Aquila-7B checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Baichuan Inc.](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baichuan-inc.md): Browse NeMo AutoModel coverage for Baichuan Inc. large language models. - [Baichuan2-13B-Chat](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baichuan-inc/Baichuan2-13B-Chat.md): Reference Baichuan2-13B-Chat checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Baichuan2-7B-Chat](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baichuan-inc/Baichuan2-7B-Chat.md): Use NeMo AutoModel to fine-tune Baichuan2-7B-Chat for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Baidu](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baidu.md): Browse NeMo AutoModel coverage for Baidu large language models. - [ERNIE-4.5-0.3B-PT](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baidu/ERNIE-4.5-0.3B-PT.md): Use ERNIE-4.5-0.3B-PT with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [ERNIE-4.5-21B-A3B-PT](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/baidu/ERNIE-4.5-21B-A3B-PT.md): Use NeMo AutoModel to fine-tune ERNIE-4.5-21B-A3B-PT for LLM workflows with checked-in text generation recipes and documented distributed settings. - [BigCode](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bigcode.md): Browse NeMo AutoModel coverage for BigCode large language models. - [starcoder](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bigcode/starcoder.md): Reference starcoder checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [starcoder2-3b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bigcode/starcoder2-3b.md): Reference starcoder2-3b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [ByteDance Seed](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bytedance-seed.md): Browse NeMo AutoModel coverage for ByteDance Seed large language models. - [Seed-Coder-8B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bytedance-seed/Seed-Coder-8B-Instruct.md): Use Seed-Coder-8B-Instruct with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Seed-OSS-36B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/bytedance-seed/Seed-OSS-36B-Instruct.md): Use NeMo AutoModel to fine-tune Seed-OSS-36B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Cohere](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/cohere.md): Browse NeMo AutoModel coverage for Cohere large language models. - [c4ai-command-r-v01](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/cohere/c4ai-command-r-v01.md): Reference c4ai-command-r-v01 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [DeepSeek AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai.md): Browse NeMo AutoModel coverage for DeepSeek AI large language models. - [deepseek-llm-7b-chat](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/deepseek-llm-7b-chat.md): Reference deepseek-llm-7b-chat checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [DeepSeek-V3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/DeepSeek-V3.md): Reference DeepSeek-V3 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [DeepSeek-V3.2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/DeepSeek-V3.2.md): Use NeMo AutoModel to fine-tune DeepSeek-V3.2 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [DeepSeek-V4-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/DeepSeek-V4-Flash.md): Use DeepSeek-V4-Flash with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [DeepSeek-V4-Pro](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/DeepSeek-V4-Pro.md): Fine-tune DeepSeek-V4-Pro with NeMo AutoModel using the checked-in multi-node recipe with pipeline and expert parallelism. - [DeepSeek-V4.1-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/deepseek-ai/DeepSeek-V4.1-Flash.md): Fine-tune DeepSeek-V4.1-Flash with NeMo AutoModel using checked-in expert-parallel text recipes and sharded Engram memory. - [EleutherAI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/eleutherai.md): Browse NeMo AutoModel coverage for EleutherAI large language models. - [gpt-j-6b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/eleutherai/gpt-j-6b.md): Reference gpt-j-6b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [gpt-neox-20b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/eleutherai/gpt-neox-20b.md): Reference gpt-neox-20b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Google](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google.md): Browse NeMo AutoModel coverage for Google large language models. - [functiongemma-270m-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/functiongemma-270m-it.md): Fine-tune functiongemma-270m-it for function-calling tasks with NeMo AutoModel using the checked-in text generation recipe. - [gemma-2-9b-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/gemma-2-9b-it.md): Use gemma-2-9b-it with NeMo AutoModel for text generation, with supported architecture details, canonical checkpoints, and recipe references. - [gemma-3-270m](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/gemma-3-270m.md): Fine-tune gemma-3-270m for text generation with NeMo AutoModel using checked-in recipes and documented distributed settings. - [gemma-4-12B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/gemma-4-12B.md): Fine-tune gemma-4-12B for text generation with NeMo AutoModel using checked-in recipes and documented distributed settings. - [gemma-4-31B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/gemma-4-31B.md): Fine-tune gemma-4-31B for text generation with NeMo AutoModel using checked-in recipes and documented distributed settings. - [gemma-7b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google/gemma-7b.md): Use gemma-7b with NeMo AutoModel for text generation, with supported architecture details, canonical checkpoints, and recipe references. - [Google T5](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google-t5.md): Browse NeMo AutoModel coverage for Google T5 large language models. - [t5-small](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/google-t5/t5-small.md): Use t5-small with NeMo AutoModel for text-to-text generation, with supported architecture details, canonical checkpoints, and recipe references. - [IBM](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/ibm.md): Browse NeMo AutoModel coverage for IBM large language models. - [granite-3.0-1b-a400m-base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/ibm/granite-3.0-1b-a400m-base.md): Reference granite-3.0-1b-a400m-base checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [granite-3.0-2b-base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/ibm/granite-3.0-2b-base.md): Reference granite-3.0-2b-base checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [IBM AI Platform](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/ibm-ai-platform.md): Browse NeMo AutoModel coverage for models published under the ibm-ai-platform Hugging Face organization. - [Bamba-9B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/ibm-ai-platform/Bamba-9B.md): Reference Bamba-9B checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Inception AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inceptionai.md): Browse NeMo AutoModel coverage for Inception AI large language models. - [jais-13b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inceptionai/jais-13b.md): Reference jais-13b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Inclusion AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inclusionai.md): Browse NeMo AutoModel coverage for Inclusion AI large language models. - [Ling-1T](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inclusionai/Ling-1T.md): Use NeMo AutoModel to fine-tune Ling-1T for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Ling-flash-2.0](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inclusionai/Ling-flash-2.0.md): Use NeMo AutoModel to fine-tune Ling-flash-2.0 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Ling-mini-2.0](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/inclusionai/Ling-mini-2.0.md): Use Ling-mini-2.0 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [InternLM](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/internlm.md): Browse NeMo AutoModel coverage for InternLM large language models. - [internlm3-8b-instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/internlm/internlm3-8b-instruct.md): Reference internlm3-8b-instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [LG AI EXAONE](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/lgai-exaone.md): Browse NeMo AutoModel coverage for LG AI EXAONE large language models. - [EXAONE-3.0-7.8B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/lgai-exaone/EXAONE-3.0-7.8B-Instruct.md): Reference EXAONE-3.0-7.8B-Instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Meta](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta.md): Browse NeMo AutoModel coverage for Meta large language models. - [Llama-3.1-70B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta/Llama-3.1-70B.md): Use NeMo AutoModel to fine-tune Llama-3.1-70B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Llama-3.1-8B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta/Llama-3.1-8B.md): Use NeMo AutoModel to fine-tune Llama-3.1-8B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Llama-3.2-1B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta/Llama-3.2-1B.md): Use Llama-3.2-1B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Llama-3.2-3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta/Llama-3.2-3B-Instruct.md): Use NeMo AutoModel to fine-tune Llama-3.2-3B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Llama-3.3-70B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta/Llama-3.3-70B-Instruct.md): Use NeMo AutoModel to fine-tune Llama-3.3-70B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Meta Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta-models.md): Browse NeMo AutoModel coverage for models published under the meta-models Hugging Face organization. - [Muse-Glimmer-30B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/meta-models/Muse-Glimmer-30B.md): Use NeMo AutoModel to fine-tune Muse-Glimmer-30B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Microsoft](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/microsoft.md): Browse NeMo AutoModel coverage for Microsoft large language models. - [phi-2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/microsoft/phi-2.md): Use phi-2 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Phi-3-mini-4k-instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/microsoft/Phi-3-mini-4k-instruct.md): Use NeMo AutoModel to fine-tune Phi-3-mini-4k-instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Phi-3-small-8k-instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/microsoft/Phi-3-small-8k-instruct.md): Reference Phi-3-small-8k-instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Phi-4](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/microsoft/Phi-4.md): Use Phi-4 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [MiniMax AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/MiniMaxAI.md): Browse NeMo AutoModel coverage for MiniMax AI large language models. - [MiniMax-M2.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/MiniMaxAI/MiniMax-M2.1.md): Use MiniMax-M2.1 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [MiniMax-M2.5](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/MiniMaxAI/MiniMax-M2.5.md): Use NeMo AutoModel to fine-tune MiniMax-M2.5 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [MiniMax-M2.7](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/MiniMaxAI/MiniMax-M2.7.md): Use NeMo AutoModel to fine-tune MiniMax-M2.7 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Mistral AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai.md): Browse NeMo AutoModel coverage for Mistral AI large language models. - [Devstral-2-123B-Instruct-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Devstral-2-123B-Instruct-2512.md): Use NeMo AutoModel to fine-tune Devstral-2-123B-Instruct-2512 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Devstral-Small-2-24B-Instruct-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Devstral-Small-2-24B-Instruct-2512.md): Use NeMo AutoModel to fine-tune Devstral-Small-2-24B-Instruct-2512 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Ministral-3-3B-Instruct-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Ministral-3-3B-Instruct-2512.md): Use Ministral-3-3B-Instruct-2512 with NeMo AutoModel for language model fine-tuning, including checkpoints, a runnable starting command, setup, and reference details. - [Mistral-7B-v0.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Mistral-7B-v0.1.md): Use Mistral-7B-v0.1 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Mistral-Nemo-Base-2407](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Mistral-Nemo-Base-2407.md): Use NeMo AutoModel to fine-tune Mistral-Nemo-Base-2407 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Mistral-Small-4-119B-2603](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Mistral-Small-4-119B-2603.md): Use NeMo AutoModel to fine-tune Mistral-Small-4-119B-2603 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Mixtral-8x7B-Instruct-v0.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Mixtral-8x7B-Instruct-v0.1.md): Use NeMo AutoModel to fine-tune Mixtral-8x7B-Instruct-v0.1 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Mixtral-8x7B-v0.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/mistralai/Mixtral-8x7B-v0.1.md): Use Mixtral-8x7B-v0.1 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Moonshot AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/moonshotai.md): Browse NeMo AutoModel coverage for Moonshot AI large language models. - [Kimi-K2-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/moonshotai/Kimi-K2-Base.md): Use NeMo AutoModel to fine-tune Kimi-K2-Base for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Kimi-K3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/moonshotai/Kimi-K3.md): Fine-tune Kimi-K3 for text generation with NeMo AutoModel using checked-in multi-node recipes with expert, pipeline, and context parallelism. - [Kimi-Linear-48B-A3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/moonshotai/Kimi-Linear-48B-A3B-Instruct.md): Use Kimi-Linear-48B-A3B-Instruct with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [Moonlight-16B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/moonshotai/Moonlight-16B-A3B.md): Fine-tune Moonlight-16B-A3B with NeMo AutoModel on 8 GPUs using FSDP2, 8-way expert parallelism, Transformer Engine, and DeepEP. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA large language models. - [Llama-3.1-Nemotron-Nano-8B-v1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/Llama-3.1-Nemotron-Nano-8B-v1.md): Use NeMo AutoModel to fine-tune Llama-3.1-Nemotron-Nano-8B-v1 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Llama-3_3-Nemotron-Super-49B-v1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/Llama-3_3-Nemotron-Super-49B-v1.md): Reference Llama-3_3-Nemotron-Super-49B-v1 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Minitron-8B-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/Minitron-8B-Base.md): Reference Minitron-8B-Base checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Nemotron-Flash-1B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/Nemotron-Flash-1B.md): Use Nemotron-Flash-1B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16.md): Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [NVIDIA-Nemotron-3-Nano-4B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16.md): Use NVIDIA-Nemotron-3-Nano-4B-BF16 with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [NVIDIA-Nemotron-3-Super-120B-A12B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16.md): Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-3-Super-120B-A12B-BF16 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16.md): Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16.md): Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [NVIDIA-Nemotron-Nano-9B-v2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/nvidia/NVIDIA-Nemotron-Nano-9B-v2.md): Use NeMo AutoModel to fine-tune NVIDIA-Nemotron-Nano-9B-v2 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [OpenAI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openai.md): Browse NeMo AutoModel coverage for OpenAI large language models. - [gpt-oss-120b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openai/gpt-oss-120b.md): Fine-tune gpt-oss-120b for text generation with NeMo AutoModel using checked-in recipes and documented distributed settings. - [gpt-oss-20b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openai/gpt-oss-20b.md): Use gpt-oss-20b with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [OpenAI Community](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openai-community.md): Browse NeMo AutoModel coverage for models published under the openai-community Hugging Face organization. - [gpt2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openai-community/gpt2.md): Pretrain gpt2 with NeMo AutoModel using a documented checkpoint, runnable recipe, setup guidance, model reference details, and links to the pretraining guide. - [OpenBMB](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openbmb.md): Browse NeMo AutoModel coverage for OpenBMB large language models. - [MiniCPM5-1B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/openbmb/MiniCPM5-1B.md): Use MiniCPM5-1B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, a runnable starting command, setup guidance, and model reference details. - [OrionStar AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/orionstar.md): Browse NeMo AutoModel coverage for OrionStar AI large language models. - [Orion-14B-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/orionstar/Orion-14B-Base.md): Reference Orion-14B-Base checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [ParaSail AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/parasail-ai.md): Browse NeMo AutoModel coverage for ParaSail AI large language models. - [GritLM-7B-vllm](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/parasail-ai/GritLM-7B-vllm.md): Reference GritLM-7B-vllm checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Poolside](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/poolside.md): Browse NeMo AutoModel coverage for Poolside large language models. - [Laguna-S-2.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/poolside/Laguna-S-2.1.md): Fine-tune Laguna-S-2.1 using the NeMo AutoModel full-SFT recipe configured for two nodes, eight GPUs per node, FSDP2, and EP16. - [Laguna-XS-2.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/poolside/Laguna-XS-2.1.md): Use NeMo AutoModel to fine-tune Laguna-XS-2.1 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen.md): Browse NeMo AutoModel coverage for Qwen large language models. - [Qwen1.5-MoE-A2.7B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen1.5-MoE-A2.7B.md): Use Qwen1.5-MoE-A2.7B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen2.5-0.5B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen2.5-0.5B.md): Use NeMo AutoModel to fine-tune Qwen2.5-0.5B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen2.5-32B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen2.5-32B-Instruct.md): Use NeMo AutoModel to fine-tune Qwen2.5-32B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen2.5-3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen2.5-3B.md): Use NeMo AutoModel to fine-tune Qwen2.5-3B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen2.5-7B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen2.5-7B-Instruct.md): Use Qwen2.5-7B-Instruct with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen3-0.6B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-0.6B.md): Use Qwen3-0.6B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen3-235B-A22B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-235B-A22B.md): Use NeMo AutoModel to fine-tune Qwen3-235B-A22B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen3-30B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-30B-A3B.md): Use Qwen3-30B-A3B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen3-32B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-32B.md): Use NeMo AutoModel to fine-tune Qwen3-32B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen3-4B-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-4B-Base.md): Use NeMo AutoModel to fine-tune Qwen3-4B-Base for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen3-8B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-8B.md): Use NeMo AutoModel to fine-tune Qwen3-8B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen3-Next-80B-A3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3-Next-80B-A3B-Instruct.md): Use Qwen3-Next-80B-A3B-Instruct with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [Qwen3.5-35B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3.5-35B-A3B.md): Use NeMo AutoModel to fine-tune Qwen3.5-35B-A3B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Qwen3.8-2.4T-A95B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3.8-2.4T-A95B.md): Fine-tune Qwen3.8-2.4T-A95B for text generation with NeMo AutoModel using checked-in multi-node expert- and pipeline-parallel recipes. - [Qwen3.8-Flash-Next](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/Qwen3.8-Flash-Next.md): Fine-tune Qwen3.8-Flash-Next for text generation with NeMo AutoModel using checked-in expert- and context-parallel recipes. - [QwQ-32B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/qwen/QwQ-32B.md): Use NeMo AutoModel to fine-tune QwQ-32B for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Stability AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/stabilityai.md): Browse NeMo AutoModel coverage for Stability AI large language models. - [stablelm-3b-4e1t](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/stabilityai/stablelm-3b-4e1t.md): Reference stablelm-3b-4e1t checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [StepFun AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/stepfun-ai.md): Browse NeMo AutoModel coverage for StepFun AI large language models. - [Step-3.5-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/stepfun-ai/Step-3.5-Flash.md): Use Step-3.5-Flash with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Tencent](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tencent.md): Browse NeMo AutoModel coverage for Tencent large language models. - [Hy-MT2-30B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tencent/Hy-MT2-30B-A3B.md): Use Hy-MT2-30B-A3B with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Hy3-preview](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tencent/Hy3-preview.md): Use Hy3-preview with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [TII](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae.md): Browse NeMo AutoModel coverage for TII large language models. - [falcon-7b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae/falcon-7b.md): Reference falcon-7b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Falcon-H1-0.5B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae/Falcon-H1-0.5B-Instruct.md): Use NeMo AutoModel to fine-tune Falcon-H1-0.5B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Falcon-H1-1.5B-Deep-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae/Falcon-H1-1.5B-Deep-Instruct.md): Use NeMo AutoModel to fine-tune Falcon-H1-1.5B-Deep-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Falcon-H1-34B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae/Falcon-H1-34B-Instruct.md): Use NeMo AutoModel to fine-tune Falcon-H1-34B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Falcon3-7B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/tiiuae/Falcon3-7B-Instruct.md): Use NeMo AutoModel to fine-tune Falcon3-7B-Instruct for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Upstage](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/upstage.md): Browse NeMo AutoModel coverage for Upstage large language models. - [solar-pro-preview-instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/upstage/solar-pro-preview-instruct.md): Reference solar-pro-preview-instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [XiaomiMiMo](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/xiaomimimo.md): Browse NeMo AutoModel coverage for XiaomiMiMo large language models. - [MiMo-V2-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/xiaomimimo/MiMo-V2-Flash.md): Fine-tune MiMo-V2-Flash and explore MiMo-V2.6-Flash-RL language and vision-language recipes, checkpoints, and settings with NeMo AutoModel. - [MiMo-V2.5-Pro](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/xiaomimimo/MiMo-V2.5-Pro.md): Fine-tune MiMo-V2.5-Pro with NeMo AutoModel using the checked-in HellaSwag recipe for its hybrid attention MoE architecture and FP8 checkpoint. - [MiMo-V2.6-Pro-RL](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/xiaomimimo/MiMo-V2.6-Pro-RL.md): Fine-tune MiMo-V2.6-Pro-RL with NeMo AutoModel using the checked-in GB200 recipes for packed Tulu3 text and MedPix-VQA vision-language data. - [Z.ai](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm.md): Browse NeMo AutoModel coverage for Z.ai large language models. - [chatglm3-6b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/chatglm3-6b.md): Reference chatglm3-6b checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [glm-4-9b-chat-hf](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/glm-4-9b-chat-hf.md): Use glm-4-9b-chat-hf with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [GLM-4.5-Air](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-4.5-Air.md): Use GLM-4.5-Air with NeMo AutoModel for language model fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [GLM-4.7](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-4.7.md): Use NeMo AutoModel to fine-tune GLM-4.7 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [GLM-5](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-5.md): Fine-tune GLM-5 through GLM-5.3 mixture-of-experts checkpoints with NeMo AutoModel using checked-in MLA and DSA recipes. - [GLM-5.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-5.1.md): Use NeMo AutoModel to fine-tune GLM-5.1 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [GLM-5.2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-5.2.md): Use NeMo AutoModel to fine-tune GLM-5.2 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [GLM-5.3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/large-language-models/thudm/GLM-5.3.md): Use NeMo AutoModel to fine-tune GLM-5.3 for LLM workflows with checked-in text generation recipes and documented distributed settings. - [Vision Language Models (VLMs)](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/overview.md): - [Cohere Labs](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/coherelabs.md): Browse NeMo AutoModel coverage for Cohere Labs vision language models. - [North-Micro-Vision-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/coherelabs/North-Micro-Vision-Instruct.md): Fine-tune North-Micro-Vision-Instruct for image-text tasks with NeMo AutoModel using the checked-in two-GPU LoRA recipe. - [DeepSeek AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/deepseek-ai.md): Browse NeMo AutoModel coverage for DeepSeek AI vision language models. - [DeepSeek-V4-Flash-Vision-Exp](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/deepseek-ai/DeepSeek-V4-Flash-Vision-Exp.md): Use NeMo AutoModel to fine-tune DeepSeek-V4-Flash-Vision-Exp for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [DeepSeek-V4.1-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/deepseek-ai/DeepSeek-V4.1-Flash.md): Use NeMo AutoModel to fine-tune DeepSeek-V4.1-Flash for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Google](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google.md): Browse NeMo AutoModel coverage for Google vision language models. - [gemma-3-4b-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-3-4b-it.md): Fine-tune gemma-3-4b-it for image-text tasks with NeMo AutoModel using checked-in full-parameter, LoRA, and distributed recipes. - [gemma-3n-E4B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-3n-E4B-it.md): Fine-tune gemma-3n-E4B-it for image-text-to-text tasks with NeMo AutoModel using checked-in recipes and distributed settings. - [gemma-4-26B-A4B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-4-26B-A4B-it.md): Fine-tune gemma-4-26B-A4B-it for image-text-to-text tasks with NeMo AutoModel using checked-in recipes and distributed settings. - [gemma-4-31B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-4-31B-it.md): Fine-tune gemma-4-31B-it for image-text tasks with NeMo AutoModel using checked-in full-parameter, LoRA, tensor-parallel, and pipeline-parallel recipes. - [gemma-4-E2B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-4-E2B-it.md): Fine-tune gemma-4-E2B-it for image-text-to-text tasks with NeMo AutoModel using checked-in recipes and distributed settings. - [gemma-4-E4B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/google/gemma-4-E4B-it.md): Fine-tune gemma-4-E4B-it for image-text-to-text tasks with NeMo AutoModel using checked-in recipes and distributed settings. - [HuggingFaceTB](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/huggingfacetb.md): Browse NeMo AutoModel coverage for models published under the HuggingFaceTB Hugging Face organization. - [SmolVLM-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/huggingfacetb/SmolVLM-Instruct.md): Reference SmolVLM-Instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [LLaVA HF](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/llava-hf.md): Browse NeMo AutoModel coverage for LLaVA HF vision language models. - [llava-1.5-7b-hf](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/llava-hf/llava-1.5-7b-hf.md): Reference llava-1.5-7b-hf checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [LMMS Lab](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/lmms-lab.md): Browse NeMo AutoModel coverage for LMMS Lab vision language models. - [LLaVA-OneVision-1.5-4B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/lmms-lab/LLaVA-OneVision-1.5-4B-Instruct.md): Use LLaVA-OneVision-1.5-4B-Instruct with NeMo AutoModel for vision-language fine-tuning, including checkpoints, runnable recipes, setup, and reference details. - [LLaVA-OneVision-1.5-8B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/lmms-lab/LLaVA-OneVision-1.5-8B-Instruct.md): Use NeMo AutoModel to fine-tune LLaVA-OneVision-1.5-8B-Instruct for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Meta](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/meta.md): Browse NeMo AutoModel coverage for Meta vision language models. - [Llama-4-Scout-17B-16E-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/meta/Llama-4-Scout-17B-16E-Instruct.md): Reference Llama-4-Scout-17B-16E-Instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Meta Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/meta-models.md): Browse NeMo AutoModel coverage for models published under the meta-models Hugging Face organization. - [Muse-Glimmer-30B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/meta-models/Muse-Glimmer-30B.md): Use Muse-Glimmer-30B with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [MiniMax AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/MiniMaxAI.md): Browse NeMo AutoModel coverage for MiniMax AI vision language models. - [MiniMax-M3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/MiniMaxAI/MiniMax-M3.md): Fine-tune MiniMax-M3 text-only on Tulu-3 or with MedPix vision-language data using NeMo AutoModel supervised fine-tuning recipes. - [Mistral AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai.md): Browse NeMo AutoModel coverage for Mistral AI vision language models. - [Devstral-2-123B-Instruct-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Devstral-2-123B-Instruct-2512.md): Fine-tune Devstral-2-123B-Instruct-2512 for text generation with NeMo AutoModel using the checked-in single-node tensor-parallel LoRA recipe. - [Ministral-3-14B-Reasoning-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Ministral-3-14B-Reasoning-2512.md): Use NeMo AutoModel to fine-tune Ministral-3-14B-Reasoning-2512 for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Ministral-3-3B-Instruct-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Ministral-3-3B-Instruct-2512.md): Reference Ministral-3-3B-Instruct-2512 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Ministral-3-8B-Reasoning-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Ministral-3-8B-Reasoning-2512.md): Use NeMo AutoModel to fine-tune Ministral-3-8B-Reasoning-2512 for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Mistral-Medium-3.5-128B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Mistral-Medium-3.5-128B.md): Use NeMo AutoModel to fine-tune Mistral-Medium-3.5-128B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Mistral-Small-4-119B-2603](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/mistralai/Mistral-Small-4-119B-2603.md): Use Mistral-Small-4-119B-2603 with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [Moonshot AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/moonshotai.md): Browse NeMo AutoModel coverage for Moonshot AI vision language models. - [Kimi-K2.5](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/moonshotai/Kimi-K2.5.md): Use NeMo AutoModel to fine-tune Kimi-K2.5 for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Kimi-K3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/moonshotai/Kimi-K3.md): Use Kimi-K3 with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Kimi-VL-A3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/moonshotai/Kimi-VL-A3B-Instruct.md): Use Kimi-VL-A3B-Instruct with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA vision language models. - [NVIDIA-Nemotron-Parse-v1.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/nvidia/NVIDIA-Nemotron-Parse-v1.1.md): Use NVIDIA-Nemotron-Parse-v1.1 with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [OpenGVLab](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/opengvlab.md): Browse NeMo AutoModel coverage for models published under the OpenGVLab Hugging Face organization. - [InternVL3_5-4B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/opengvlab/InternVL3_5-4B.md): Use InternVL3_5-4B with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen.md): Browse NeMo AutoModel coverage for Qwen vision language models. - [Qwen2.5-VL-3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen2.5-VL-3B-Instruct.md): Use Qwen2.5-VL-3B-Instruct with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [Qwen3-VL-235B-A22B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3-VL-235B-A22B-Instruct.md): Use NeMo AutoModel to fine-tune Qwen3-VL-235B-A22B-Instruct for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3-VL-30B-A3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3-VL-30B-A3B-Instruct.md): Use NeMo AutoModel to fine-tune Qwen3-VL-30B-A3B-Instruct for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3-VL-4B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3-VL-4B-Instruct.md): Reference Qwen3-VL-4B-Instruct checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Qwen3-VL-8B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3-VL-8B-Instruct.md): Use NeMo AutoModel to fine-tune Qwen3-VL-8B-Instruct for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.5-122B-A10B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-122B-A10B.md): Use NeMo AutoModel to fine-tune Qwen3.5-122B-A10B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.5-27B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-27B.md): Use NeMo AutoModel to fine-tune Qwen3.5-27B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.5-35B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-35B-A3B.md): Use NeMo AutoModel to fine-tune Qwen3.5-35B-A3B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.5-397B-A17B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-397B-A17B.md): Use NeMo AutoModel to fine-tune Qwen3.5-397B-A17B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.5-4B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-4B.md): Use Qwen3.5-4B with NeMo AutoModel for vision-language fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen3.5-9B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.5-9B.md): Use NeMo AutoModel to fine-tune Qwen3.5-9B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.6-27B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.6-27B.md): Fine-tune Qwen3.6-27B for vision-language tasks with NeMo AutoModel using checked-in full-parameter and LoRA recipes with distributed settings. - [Qwen3.6-35B-A3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.6-35B-A3B.md): Use NeMo AutoModel to fine-tune Qwen3.6-35B-A3B for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Qwen3.8-27B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/qwen/Qwen3.8-27B.md): Fine-tune Qwen3.8-27B for vision-language tasks with NeMo AutoModel using checked-in full-parameter and LoRA recipes with distributed settings. - [StepFun AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/stepfun-ai.md): Browse NeMo AutoModel coverage for StepFun AI vision language models. - [Step-3.7-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/stepfun-ai/Step-3.7-Flash.md): Fine-tune Step-3.7-Flash on MedPix with full or LoRA vision-language recipes in NeMo AutoModel for supervised image-text training. - [Thinking Machines](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/thinkingmachines.md): Browse NeMo AutoModel coverage for Thinking Machines vision language models. - [Inkling](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/thinkingmachines/Inkling.md): Fine-tune Inkling vision-language checkpoints with NeMo AutoModel using checked-in multi-node recipes with expert and pipeline parallelism. - [Inkling-Small](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/thinkingmachines/Inkling-Small.md): Use NeMo AutoModel to fine-tune Inkling-Small for VLM workflows with checked-in image-text-to-text recipes and documented distributed settings. - [Z.ai](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/thudm.md): Browse NeMo AutoModel coverage for Z.ai vision language models. - [GLM-5.3-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/vision-language-models/thudm/GLM-5.3-Flash.md): Fine-tune GLM-5.3-Flash for vision-language tasks with NeMo AutoModel using a checked-in packed-context and expert-parallel recipe. - [Multimodal Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/multimodal/overview.md): - [ByteDance Seed](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/multimodal/bytedance-seed.md): Browse NeMo AutoModel coverage for ByteDance Seed multimodal models. - [BAGEL-7B-MoT](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/multimodal/bytedance-seed/BAGEL-7B-MoT.md): Use BAGEL-7B-MoT with NeMo AutoModel for multimodal pretraining, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Omni Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/overview.md): - [Microsoft](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/microsoft.md): Browse NeMo AutoModel coverage for Microsoft omni models. - [Phi-4-multimodal-instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/microsoft/Phi-4-multimodal-instruct.md): Use Phi-4-multimodal-instruct with NeMo AutoModel for multimodal fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA omni models. - [Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16.md): Use Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16 with NeMo AutoModel for multimodal fine-tuning, including checkpoints, runnable recipes, setup, and reference details. - [NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16.md): Use NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16 with NeMo AutoModel for multimodal fine-tuning, with checkpoints, recipes, setup, and reference details. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/qwen.md): Browse NeMo AutoModel coverage for Qwen omni models. - [Qwen2.5-Omni-3B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/qwen/Qwen2.5-Omni-3B.md): Use Qwen2.5-Omni-3B with NeMo AutoModel for multimodal fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [Qwen2.5-Omni-7B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/qwen/Qwen2.5-Omni-7B.md): Use NeMo AutoModel to fine-tune Qwen2.5-Omni-7B for Omni workflows with checked-in any to any recipes and documented distributed settings. - [Qwen3-Omni-30B-A3B-Instruct](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/omni/qwen/Qwen3-Omni-30B-A3B-Instruct.md): Use Qwen3-Omni-30B-A3B-Instruct with NeMo AutoModel for multimodal fine-tuning, with documented checkpoints, runnable recipes, setup, and model reference details. - [Diffusion Language Models (dLLMs)](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/overview.md): - [Google](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/google.md): Browse NeMo AutoModel coverage for Google diffusion language models. - [diffusiongemma-26B-A4B-it](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/google/diffusiongemma-26B-A4B-it.md): Use diffusiongemma-26B-A4B-it with NeMo AutoModel for diffusion language model fine-tuning, including checkpoints, runnable recipes, setup, and reference details. - [GSAI ML](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/gsai-ml.md): Browse NeMo AutoModel coverage for GSAI ML diffusion language models. - [LLaDA-8B-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/gsai-ml/LLaDA-8B-Base.md): Fine-tune LLaDA-8B-Base as a diffusion language model with NeMo AutoModel using checked-in full-parameter and LoRA recipes. - [Inclusion AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/inclusionai.md): Browse NeMo AutoModel coverage for Inclusion AI diffusion language models. - [LLaDA2.1-mini](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/inclusionai/LLaDA2.1-mini.md): Fine-tune LLaDA2.1-mini as a mixture-of-experts diffusion language model with NeMo AutoModel using full-parameter and LoRA recipes. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA diffusion language models. - [Nemotron-Labs-Diffusion-8B-Base](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/nvidia/Nemotron-Labs-Diffusion-8B-Base.md): Fine-tune Nemotron-Labs-Diffusion-8B-Base with NeMo AutoModel using checked-in full-parameter and LoRA diffusion language model recipes. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/qwen.md): Browse NeMo AutoModel coverage for Qwen diffusion language models. - [Qwen3-8B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/qwen/Qwen3-8B.md): Convert and fine-tune Qwen3-8B as a diffusion language model with NeMo AutoModel using the checked-in I-DLM recipe and text checkpoint. - [Z Lab](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/z-lab.md): Browse NeMo AutoModel coverage for Z Lab diffusion language models. - [Qwen3-4B-DFlash-b16](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/dllm/z-lab/Qwen3-4B-DFlash-b16.md): Train Qwen3-4B-DFlash-b16 as a speculative-decoding draft model with NeMo AutoModel using the checked-in DFlash recipe and frozen Qwen3 target. - [Diffusion Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/overview.md): - [Black Forest Labs](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/black-forest-labs.md): Browse NeMo AutoModel coverage for Black Forest Labs diffusion models. - [FLUX.1-dev](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/black-forest-labs/FLUX.1-dev.md): Use FLUX.1-dev with NeMo AutoModel for diffusion training and fine-tuning, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [FLUX.2-dev](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/black-forest-labs/FLUX.2-dev.md): Fine-tune FLUX.2-dev for text-to-image generation with NeMo AutoModel using checked-in full-parameter and LoRA flow-matching recipes. - [Diffusers](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/diffusers.md): Browse NeMo AutoModel coverage for Diffusers diffusion models. - [LTX-2.3-Diffusers](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/diffusers/LTX-2.3-Diffusers.md): Fine-tune LTX-2.3-Diffusers for text-to-video generation with NeMo AutoModel using checked-in full-parameter and LoRA flow-matching recipes. - [HunyuanVideo Community](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/hunyuanvideo-community.md): Browse NeMo AutoModel coverage for HunyuanVideo Community diffusion models. - [HunyuanVideo-1.5-Diffusers-720p_t2v](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-720p_t2v.md): Use HunyuanVideo-1.5-Diffusers-720p_t2v with NeMo AutoModel for diffusion training and fine-tuning, including checkpoints, runnable recipes, setup, and reference details. - [Lightricks](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/lightricks.md): Browse NeMo AutoModel coverage for Lightricks diffusion models. - [LTX-2.3](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/lightricks/LTX-2.3.md): Fine-tune LTX-2.3 for synchronized video and audio generation with NeMo AutoModel using full-parameter, LoRA, and generation recipes. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/qwen.md): Browse NeMo AutoModel coverage for Qwen diffusion models. - [Qwen-Image](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/qwen/Qwen-Image.md): Train Qwen-Image text-to-image and image-editing checkpoints with NeMo AutoModel using checked-in flow-matching and generation recipes. - [Qwen-Image-2.1](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/qwen/Qwen-Image-2.1.md): Fine-tune Qwen-Image-2.1 text-to-image checkpoints with NeMo AutoModel using checked-in full-parameter and LoRA flow-matching recipes. - [Qwen-Image-Edit-2511](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/qwen/Qwen-Image-Edit-2511.md): Use NeMo AutoModel to fine-tune Qwen-Image-Edit-2511 for Diffusion workflows with checked-in image to image recipes and documented distributed settings. - [Tencent](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/tencent.md): Browse NeMo AutoModel coverage for Tencent diffusion models. - [HunyuanImage-3.0](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/tencent/HunyuanImage-3.0.md): Fine-tune tencent/HunyuanImage-3.0, an 80B MoE text-to-image transformer, with LoRA and expert parallelism in NeMo AutoModel. - [Wan AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/wan-ai.md): Browse NeMo AutoModel coverage for Wan AI diffusion models. - [Wan2.1-T2V-1.3B-Diffusers](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/wan-ai/Wan2.1-T2V-1.3B-Diffusers.md): Reference Wan2.1-T2V-1.3B-Diffusers checkpoint and architecture details for NeMo AutoModel, with setup guidance and related training recipes. - [Wan2.1-T2V-14B-Diffusers](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/wan-ai/Wan2.1-T2V-14B-Diffusers.md): Use NeMo AutoModel to fine-tune Wan2.1-T2V-14B-Diffusers for Diffusion workflows with checked-in text to video recipes and documented distributed settings. - [Wan2.2-T2V-A14B-Diffusers](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/diffusion/wan-ai/Wan2.2-T2V-A14B-Diffusers.md): Use Wan2.2-T2V-A14B-Diffusers with NeMo AutoModel for diffusion training and fine-tuning, including checkpoints, runnable recipes, setup, and reference details. - [Embedding Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/overview.md): Overview of NeMo AutoModel embedding models, including bidirectional Llama and Ministral3 backbones, Hugging Face AutoModel fallback, and bi-encoder recipes. - [Meta](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/meta.md): Browse NeMo AutoModel coverage for models published by Meta for embedding workflows. - [Llama-3.2-1B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/meta/Llama-3.2-1B.md): Use NeMo AutoModel to fine-tune Llama-3.2-1B for Embedding workflows with checked-in feature extraction recipes and documented distributed settings. - [Mistral AI](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/mistralai.md): Browse NeMo AutoModel coverage for Mistral AI embedding models. - [Ministral-3-3B-Base-2512](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/mistralai/Ministral-3-3B-Base-2512.md): Reference Ministral-3-3B-Base-2512 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA embedding models. - [llama-embed-nemotron-8b](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/nvidia/llama-embed-nemotron-8b.md): Use llama-embed-nemotron-8b with NeMo AutoModel for embedding training, with documented checkpoints, runnable recipes, setup guidance, and model reference details. - [llama-nemotron-embed-vl-1b-v2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/embedding-models/nvidia/llama-nemotron-embed-vl-1b-v2.md): Extract multimodal embeddings with llama-nemotron-embed-vl-1b-v2 in NeMo AutoModel using the checked-in bi-encoder recipe and DDP. - [Reranking Models](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/reranking-models/overview.md): Reranking model coverage in NeMo AutoModel, including optimized Llama and Qwen3 backbones, Hugging Face Auto fallback, and supported workflows. - [NVIDIA](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/reranking-models/nvidia.md): Browse NeMo AutoModel coverage for NVIDIA reranking models. - [llama-nemotron-rerank-1b-v2](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/reranking-models/nvidia/llama-nemotron-rerank-1b-v2.md): Reference llama-nemotron-rerank-1b-v2 checkpoint and architecture details for NeMo AutoModel, with model-family information, setup guidance, and upstream resources. - [Qwen](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/reranking-models/qwen.md): Browse NeMo AutoModel coverage for Qwen reranking models. - [Qwen3-Reranker-4B](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/reranking-models/qwen/Qwen3-Reranker-4B.md): Train Qwen3-Reranker-4B with NeMo AutoModel using context-aware query-document scoring, compatible checkpoint loading, and the retrieval training recipe. - [Troubleshooting](https://docs.nvidia.com/nemo/automodel/v0.7/model-coverage/troubleshooting.md): Diagnose model-loading failures and checkpoint-specific training instability. - [Tutorials](https://docs.nvidia.com/nemo/automodel/v0.7/tutorials/overview.md): Follow NeMo AutoModel walkthroughs for specific language, vision-language, multimodal, and audio models and tasks. - [Function Calling with NeMo AutoModel using FunctionGemma](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/function-calling.md): - [Multi-Turn Agent (Tool-Calling) SFT with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/agent-sft.md): End-to-end multi-turn, function-calling SFT on Qwen2.5-3B with the glaive_toolcall and SynthTraces datasets - [LLM Pre-Training with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/nanogpt-pretraining.md): - [DeepSeek-V4 Flash](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/deepseek-v4-flash.md): - [Hy3-preview](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/hy3-preview.md): - [Fine-Tune Nemotron-3-Ultra-550B](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/nemotron-3-ultra.md): End-to-end LoRA PEFT fine-tuning of Nemotron-3-Ultra-550B on HellaSwag using NeMo AutoModel on GB200 and H100. - [Fine-Tuning DiffusionGemma](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/diffusiongemma.md): Supervised fine-tuning of DiffusionGemma 26B-A4B with full SFT and LoRA on NeMo AutoModel. - [Fine-Tune Gemma 3 and Gemma 3n](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/gemma-3-3n.md): - [Fine-Tune Gemma 4 31B on CORD-v2 Receipts โ€” End-to-End Guide](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/gemma-4.md): - [Fine-Tune Qwen3.5-VL](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/qwen3-5-vl.md): - [Fine-Tune Qwen3.8-27B](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/qwen3-8-27b.md): End-to-end full SFT and LoRA recipes for Qwen3.8-27B on MedPix-VQA. - [Nemotron-Omni](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/nemotron-omni.md): - [Mistral Medium 3.5 VL](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/mistral-medium-3-5.md): - [MiniMax-M3](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/minimax-m3.md) - [Fine-Tune Step-3.7-Flash](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/step-3-7.md): End-to-end SFT and LoRA setup for Stepfun AI's Step-3.7-Flash 198B-A13B MoE vision-language model. - [Fine-Tune Qwen3-Omni for ASR](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/qwen3-omni-asr.md): End-to-end ASR fine-tuning of Qwen3-Omni-30B on Hugging Face audio datasets with NeMo AutoModel. - [Training Recipes](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/overview.md): Choose a reusable NeMo AutoModel training workflow and find example configurations for fine-tuning, pretraining, distillation, retrieval, and diffusion models. - [Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/sft-peft.md): Fine-tune language models with NeMo AutoModel using SFT or PEFT (LoRA), from install and YAML config through training, evaluation, publish, and vLLM deploy. - [Pretrain Megatron Core Datasets with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/pretraining.md): - [Knowledge Distillation with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/knowledge-distillation.md): - [Sequence Classification (SFT/PEFT) with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/sequence-classification.md): Train a sequence classification model with NeMo AutoModel using GLUE MRPC, RoBERTa, and optional LoRA. - [Retrieval Fine-Tuning (Bi-Encoder and Cross-Encoder)](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/retrieval-finetune.md): Fine-tune bi-encoder and cross-encoder retrieval models in NeMo AutoModel with distributed training, low-rank adaptation (LoRA), hard-negative mining, and evaluation. - [Fine-Tune Large MoE LLMs](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/large-moe-fine-tuning.md): Fine-tune large Mixture-of-Experts (MoE) LLMs with NeMo AutoModel using HellaSwag recipes for MiniMax-M2.5, GLM-5, Step-3.5 Flash, and DeepSeek-V3.2. - [Diffusion Model Fine-Tuning with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/diffusion-fine-tuning.md): Fine-tune text-to-image and text-to-video diffusion models with NeMo AutoModel using flow matching, from dataset prep through multi-node training and inference. - [dLLM Fine-Tuning](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/dllm-fine-tuning.md): Fine-tune diffusion language models (dLLMs), including LLaDA, DiffusionGemma, DFlash, and I-DLM, with NeMo AutoModel. - [Quantization-Aware Training (QAT) in NeMo Automodel](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/qat.md): - [Train an EAGLE Drafter for Speculative Decoding โ€” End-to-End Guide](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/eagle-speculative-decoding.md): Step-by-step guide for training EAGLE-3 and EAGLE-1 speculative decoding drafters with NeMo AutoModel, from data preparation through SGLang serving. - [Train a DFlash Drafter for Speculative Decoding](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/dflash-speculative-decoding.md): Train a DFlash block-parallel speculative-decoding drafter with NeMo AutoModel, from data through multi-GPU training, including the DFlash 2, Domino, and JetSpec variants. - [Train a DSpark Drafter for Speculative Decoding](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/dspark-speculative-decoding.md): Train a DSpark semi-autoregressive speculative-decoding drafter with NeMo AutoModel, from data through 2-GPU FSDP2 training. - [Dataset Overview: LLM, VLM, and Retrieval Datasets in NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/overview.md): - [Integrate Your Own Text Dataset](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/text-dataset.md): - [Retrieval Dataset](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/retrieval-dataset.md): Prepare raw or normalized datasets for bi-encoder and cross-encoder fine-tuning. - [Use the ColumnMappedTextInstructionDataset](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/columnmapped-dataset.md): - [Use the ColumnMappedTextInstructionIterableDataset (Streaming)](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/columnmapped-iterable.md): - [Integrate Your Own Multi-Modal Dataset](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/multi-modal-dataset.md): - [Diffusion Dataset Preparation](https://docs.nvidia.com/nemo/automodel/v0.7/datasets/diffusion-dataset.md): - [Job Launchers](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/overview.md): - [Run on Your Local Workstation](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/local-workstation.md): - [Run on a Cluster](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/slurm-cluster.md): - [Run with NeMo-Run](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/nemo-run.md): - [Run on Any Cloud with SkyPilot](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/skypilot.md): - [SkyPilot k8s](https://docs.nvidia.com/nemo/automodel/v0.7/job-launchers/skypilot-k8s.md): - [Model Training on Databricks](https://docs.nvidia.com/nemo/automodel/v0.7/recipes-e2e-examples/databricks.md): - [Checkpointing in NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/development/checkpointing.md): Save and manage NeMo AutoModel checkpoints in Safetensors and PyTorch DCP formats, including consolidated and sharded layouts, PEFT adapters, asynchronous saves, and preemption handling. - [Use Gradient (Activation) Checkpointing](https://docs.nvidia.com/nemo/automodel/v0.7/development/gradient-checkpointing.md): - [Distributed Setup (Python API)](https://docs.nvidia.com/nemo/automodel/v0.7/development/distributed-setup.md): Configure tensor, pipeline, context, and expert parallelism for NeMoAutoModel* loaders with the typed DistributedSetup object. - [Pipeline Parallelism with AutoPipeline](https://docs.nvidia.com/nemo/automodel/v0.7/development/pipeline-parallelism.md): Configure AutoPipeline for Hugging Face models, mix pipeline parallelism with other strategies, and debug pipeline stages. - [Context-Parallel Vision Frame Sharding](https://docs.nvidia.com/nemo/automodel/v0.7/development/cp-vision-frame-sharding.md): Reduce duplicated vision-tower work by distributing image and video frames across context-parallel ranks. - [FP8 Training in NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/development/fp8-training.md): - [Mixed-Precision Training](https://docs.nvidia.com/nemo/automodel/v0.7/development/mixed-precision-training.md): Recommended dtype patterns for fp32 master weights and optimizer state, bf16 compute, and FSDP2 mixed precision in NeMo AutoModel. - [MLflow Logging in NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.7/development/mlflow-logging.md): - [Breaking Changes](https://docs.nvidia.com/nemo/automodel/v0.7/development/breaking-changes.md): - [API Reference](https://docs.nvidia.com/nemo/automodel/v0.7/reference/api-reference.md): Auto-generated Python API reference for the nemo_automodel library. - [Model Parallelizer API](https://docs.nvidia.com/nemo/automodel/v0.7/reference/model-parallelizer.md): Implement model-owned parallelization policy without duplicating NeMo AutoModel's distributed runtime. - [nemo_automodel](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel.md) - [nemo_automodel.autonvtx](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/autonvtx.md) - [nemo_automodel.cli](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/cli.md) - [nemo_automodel.cli.app](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/cli/app.md) - [nemo_automodel.cli.query_capabilities](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/cli/query_capabilities.md) - [nemo_automodel.cli.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/cli/utils.md) - [nemo_automodel.components](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components.md) - [nemo_automodel.components.attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention.md) - [nemo_automodel.components.attention.dflash_mask](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention/dflash_mask.md) - [nemo_automodel.components.attention.ffpa_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention/ffpa_attention.md) - [nemo_automodel.components.attention.flex_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention/flex_attention.md) - [nemo_automodel.components.attention.idlm_mask](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention/idlm_mask.md) - [nemo_automodel.components.attention.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/attention/utils.md) - [nemo_automodel.components.checkpoint](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint.md) - [nemo_automodel.components.checkpoint.addons](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/addons.md) - [nemo_automodel.components.checkpoint.checkpointing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/checkpointing.md) - [nemo_automodel.components.checkpoint.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/config.md) - [nemo_automodel.components.checkpoint.conversion_mapping](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/conversion_mapping.md) - [nemo_automodel.components.checkpoint.lifecycle](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/lifecycle.md) - [nemo_automodel.components.checkpoint.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/state_dict_adapter.md) - [nemo_automodel.components.checkpoint.stateful_wrappers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/stateful_wrappers.md) - [nemo_automodel.components.checkpoint.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/checkpoint/utils.md) - [nemo_automodel.components.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/config.md) - [nemo_automodel.components.config.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/config/loader.md) - [nemo_automodel.components.cuda_graphs](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/cuda_graphs.md) - [nemo_automodel.components.cuda_graphs.partial](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/cuda_graphs/partial.md) - [nemo_automodel.components.datasets](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets.md) - [nemo_automodel.components.datasets.audio](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/audio.md) - [nemo_automodel.components.datasets.audio.collate_fns](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/audio/collate_fns.md) - [nemo_automodel.components.datasets.audio.datasets](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/audio/datasets.md) - [nemo_automodel.components.datasets.audio.multi_en](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/audio/multi_en.md) - [nemo_automodel.components.datasets.datum](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/datum.md) - [nemo_automodel.components.datasets.diffusion](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion.md) - [nemo_automodel.components.datasets.diffusion.base_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/base_dataset.md) - [nemo_automodel.components.datasets.diffusion.collate_fns](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/collate_fns.md) - [nemo_automodel.components.datasets.diffusion.image_edit_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/image_edit_dataset.md) - [nemo_automodel.components.datasets.diffusion.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/loader.md) - [nemo_automodel.components.datasets.diffusion.meta_files_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/meta_files_dataset.md) - [nemo_automodel.components.datasets.diffusion.mock_dataloader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/mock_dataloader.md) - [nemo_automodel.components.datasets.diffusion.multi_tier_bucketing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/multi_tier_bucketing.md) - [nemo_automodel.components.datasets.diffusion.sampler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/sampler.md) - [nemo_automodel.components.datasets.diffusion.text_to_image_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/text_to_image_dataset.md) - [nemo_automodel.components.datasets.diffusion.text_to_video_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/diffusion/text_to_video_dataset.md) - [nemo_automodel.components.datasets.dllm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/dllm.md) - [nemo_automodel.components.datasets.dllm.collate](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/dllm/collate.md) - [nemo_automodel.components.datasets.dllm.corruption](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/dllm/corruption.md) - [nemo_automodel.components.datasets.lazy_mapped_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/lazy_mapped_dataset.md) - [nemo_automodel.components.datasets.llm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm.md) - [nemo_automodel.components.datasets.llm.agent_chat](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/agent_chat.md) - [nemo_automodel.components.datasets.llm.chat_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/chat_dataset.md) - [nemo_automodel.components.datasets.llm.column_mapped_text_instruction_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/column_mapped_text_instruction_dataset.md) - [nemo_automodel.components.datasets.llm.column_mapped_text_instruction_iterable_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/column_mapped_text_instruction_iterable_dataset.md) - [nemo_automodel.components.datasets.llm.delta_lake_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/delta_lake_dataset.md) - [nemo_automodel.components.datasets.llm.dspark_cache](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/dspark_cache.md) - [nemo_automodel.components.datasets.llm.eagle3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/eagle3.md) - [nemo_automodel.components.datasets.llm.eagle3_cache](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/eagle3_cache.md) - [nemo_automodel.components.datasets.llm.formatting_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/formatting_utils.md) - [nemo_automodel.components.datasets.llm.hellaswag](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/hellaswag.md) - [nemo_automodel.components.datasets.llm.length_grouped_sampler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/length_grouped_sampler.md) - [nemo_automodel.components.datasets.llm.megatron](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron.md) - [nemo_automodel.components.datasets.llm.megatron.builder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/builder.md) - [nemo_automodel.components.datasets.llm.megatron.gpt_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/gpt_dataset.md) - [nemo_automodel.components.datasets.llm.megatron.helpers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/helpers.md) - [nemo_automodel.components.datasets.llm.megatron.indexed_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/indexed_dataset.md) - [nemo_automodel.components.datasets.llm.megatron.megatron_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/megatron_utils.md) - [nemo_automodel.components.datasets.llm.megatron.sampler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron/sampler.md) - [nemo_automodel.components.datasets.llm.megatron_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/megatron_dataset.md) - [nemo_automodel.components.datasets.llm.mock](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/mock.md) - [nemo_automodel.components.datasets.llm.mock_iterable_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/mock_iterable_dataset.md) - [nemo_automodel.components.datasets.llm.mock_packed](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/mock_packed.md) - [nemo_automodel.components.datasets.llm.mock_prefix_tree](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/mock_prefix_tree.md) - [nemo_automodel.components.datasets.llm.mock_seq_cls](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/mock_seq_cls.md) - [nemo_automodel.components.datasets.llm.nanogpt_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/nanogpt_dataset.md) - [nemo_automodel.components.datasets.llm.neat_packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/neat_packing.md) - [nemo_automodel.components.datasets.llm.offline_cache](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/offline_cache.md) - [nemo_automodel.components.datasets.llm.packed_sequence](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/packed_sequence.md) - [nemo_automodel.components.datasets.llm.prefix_tree](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/prefix_tree.md) - [nemo_automodel.components.datasets.llm.retrieval_collator](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/retrieval_collator.md) - [nemo_automodel.components.datasets.llm.retrieval_dataset](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/retrieval_dataset.md) - [nemo_automodel.components.datasets.llm.retrieval_dataset_inline](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/retrieval_dataset_inline.md) - [nemo_automodel.components.datasets.llm.retrieval_dataset_normalized](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/retrieval_dataset_normalized.md) - [nemo_automodel.components.datasets.llm.retrieval_distill_collator](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/retrieval_distill_collator.md) - [nemo_automodel.components.datasets.llm.seq_cls](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/seq_cls.md) - [nemo_automodel.components.datasets.llm.seq2seq](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/seq2seq.md) - [nemo_automodel.components.datasets.llm.squad](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/squad.md) - [nemo_automodel.components.datasets.llm.xlam](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/llm/xlam.md) - [nemo_automodel.components.datasets.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/loader.md) - [nemo_automodel.components.datasets.multimodal](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal.md) - [nemo_automodel.components.datasets.multimodal.collate_fns](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/collate_fns.md) - [nemo_automodel.components.datasets.multimodal.datasets](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/datasets.md) - [nemo_automodel.components.datasets.multimodal.distributed_iterable](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/distributed_iterable.md) - [nemo_automodel.components.datasets.multimodal.interleave](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/interleave.md) - [nemo_automodel.components.datasets.multimodal.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/loader.md) - [nemo_automodel.components.datasets.multimodal.packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/packing.md) - [nemo_automodel.components.datasets.multimodal.parquet_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/parquet_utils.md) - [nemo_automodel.components.datasets.multimodal.transforms](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/transforms.md) - [nemo_automodel.components.datasets.multimodal.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/utils.md) - [nemo_automodel.components.datasets.multimodal.video](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/multimodal/video.md) - [nemo_automodel.components.datasets.packed_seq](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/packed_seq.md) - [nemo_automodel.components.datasets.packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/packing.md) - [nemo_automodel.components.datasets.reservoir_sampler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/reservoir_sampler.md) - [nemo_automodel.components.datasets.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/utils.md) - [nemo_automodel.components.datasets.vlm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm.md) - [nemo_automodel.components.datasets.vlm.collate_fns](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/collate_fns.md) - [nemo_automodel.components.datasets.vlm.datasets](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/datasets.md) - [nemo_automodel.components.datasets.vlm.dspark_collate](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/dspark_collate.md) - [nemo_automodel.components.datasets.vlm.fake_image](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/fake_image.md) - [nemo_automodel.components.datasets.vlm.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/loader.md) - [nemo_automodel.components.datasets.vlm.mock](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/mock.md) - [nemo_automodel.components.datasets.vlm.neat_packing_vlm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/neat_packing_vlm.md) - [nemo_automodel.components.datasets.vlm.pp_media](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/pp_media.md) - [nemo_automodel.components.datasets.vlm.samplers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/samplers.md) - [nemo_automodel.components.datasets.vlm.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/datasets/vlm/utils.md) - [nemo_automodel.components.distributed](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed.md) - [nemo_automodel.components.distributed.activation_checkpointing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/activation_checkpointing.md) - [nemo_automodel.components.distributed.blockdiag_cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp.md) - [nemo_automodel.components.distributed.blockdiag_cp.batch](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/batch.md) - [nemo_automodel.components.distributed.blockdiag_cp.exchange](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/exchange.md) - [nemo_automodel.components.distributed.blockdiag_cp.kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/kernels.md) - [nemo_automodel.components.distributed.blockdiag_cp.packed](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/packed.md) - [nemo_automodel.components.distributed.blockdiag_cp.runtime](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/runtime.md) - [nemo_automodel.components.distributed.blockdiag_cp.state](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/blockdiag_cp/state.md) - [nemo_automodel.components.distributed.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/config.md) - [nemo_automodel.components.distributed.context_parallel](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/context_parallel.md) - [nemo_automodel.components.distributed.context_parallel.magi](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/context_parallel/magi.md) - [nemo_automodel.components.distributed.context_parallel.mamba](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/context_parallel/mamba.md) - [nemo_automodel.components.distributed.context_parallel.sharder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/context_parallel/sharder.md) - [nemo_automodel.components.distributed.context_parallel.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/context_parallel/utils.md) - [nemo_automodel.components.distributed.cp_vision_frame_shard](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/cp_vision_frame_shard.md) - [nemo_automodel.components.distributed.ddp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/ddp.md) - [nemo_automodel.components.distributed.fsdp_patches](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/fsdp_patches.md) - [nemo_automodel.components.distributed.fsdp2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/fsdp2.md) - [nemo_automodel.components.distributed.grad_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/grad_utils.md) - [nemo_automodel.components.distributed.init_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/init_utils.md) - [nemo_automodel.components.distributed.megatron_fsdp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/megatron_fsdp.md) - [nemo_automodel.components.distributed.mesh](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/mesh.md) - [nemo_automodel.components.distributed.mesh_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/mesh_utils.md) - [nemo_automodel.components.distributed.model_parallelizer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/model_parallelizer.md) - [nemo_automodel.components.distributed.multimodal_fsdp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/multimodal_fsdp.md) - [nemo_automodel.components.distributed.optimized_tp_plans](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/optimized_tp_plans.md) - [nemo_automodel.components.distributed.parallel_styles](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/parallel_styles.md) - [nemo_automodel.components.distributed.parallelizer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/parallelizer.md) - [nemo_automodel.components.distributed.parallelizer_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/parallelizer_utils.md) - [nemo_automodel.components.distributed.pipelining](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining.md) - [nemo_automodel.components.distributed.pipelining.autopipeline](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/autopipeline.md) - [nemo_automodel.components.distributed.pipelining.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/config.md) - [nemo_automodel.components.distributed.pipelining.functional](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/functional.md) - [nemo_automodel.components.distributed.pipelining.hf_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/hf_utils.md) - [nemo_automodel.components.distributed.pipelining.recv_buffer_pool](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/recv_buffer_pool.md) - [nemo_automodel.components.distributed.pipelining.runtime](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/pipelining/runtime.md) - [nemo_automodel.components.distributed.tensor_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/tensor_utils.md) - [nemo_automodel.components.distributed.thd_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/thd_utils.md) - [nemo_automodel.components.distributed.tp_replicas](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/tp_replicas.md) - [nemo_automodel.components.distributed.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/distributed/utils.md) - [nemo_automodel.components.eval](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/eval.md) - [nemo_automodel.components.eval.tool_call_evaluator](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/eval/tool_call_evaluator.md) - [nemo_automodel.components.eval.tool_call_parser](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/eval/tool_call_parser.md) - [nemo_automodel.components.flow_matching](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching.md) - [nemo_automodel.components.flow_matching.adapters](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters.md) - [nemo_automodel.components.flow_matching.adapters.base](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/base.md) - [nemo_automodel.components.flow_matching.adapters.flux](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/flux.md) - [nemo_automodel.components.flow_matching.adapters.flux2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/flux2.md) - [nemo_automodel.components.flow_matching.adapters.flux3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/flux3.md) - [nemo_automodel.components.flow_matching.adapters.hunyuan](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/hunyuan.md) - [nemo_automodel.components.flow_matching.adapters.ltx2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/ltx2.md) - [nemo_automodel.components.flow_matching.adapters.qwen_image](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/qwen_image.md) - [nemo_automodel.components.flow_matching.adapters.qwen_image_21](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/qwen_image_21.md) - [nemo_automodel.components.flow_matching.adapters.simple](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/adapters/simple.md) - [nemo_automodel.components.flow_matching.pipeline](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/pipeline.md) - [nemo_automodel.components.flow_matching.time_shift_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/flow_matching/time_shift_utils.md) - [nemo_automodel.components.launcher](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher.md) - [nemo_automodel.components.launcher.base](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/base.md) - [nemo_automodel.components.launcher.interactive](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/interactive.md) - [nemo_automodel.components.launcher.nemo_run](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/nemo_run.md) - [nemo_automodel.components.launcher.nemo_run.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/nemo_run/config.md) - [nemo_automodel.components.launcher.nemo_run.launcher](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/nemo_run/launcher.md) - [nemo_automodel.components.launcher.nemo_run.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/nemo_run/utils.md) - [nemo_automodel.components.launcher.skypilot](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/skypilot.md) - [nemo_automodel.components.launcher.skypilot.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/skypilot/config.md) - [nemo_automodel.components.launcher.skypilot.launcher](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/skypilot/launcher.md) - [nemo_automodel.components.launcher.skypilot.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/launcher/skypilot/utils.md) - [nemo_automodel.components.loggers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers.md) - [nemo_automodel.components.loggers.comet_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/comet_utils.md) - [nemo_automodel.components.loggers.log_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/log_utils.md) - [nemo_automodel.components.loggers.loggers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/loggers.md) - [nemo_automodel.components.loggers.metric_logger](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/metric_logger.md) - [nemo_automodel.components.loggers.mlflow_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/mlflow_utils.md) - [nemo_automodel.components.loggers.trackio_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/trackio_utils.md) - [nemo_automodel.components.loggers.wandb_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loggers/wandb_utils.md) - [nemo_automodel.components.loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss.md) - [nemo_automodel.components.loss.chunked_ce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/chunked_ce.md) - [nemo_automodel.components.loss.dist_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/dist_utils.md) - [nemo_automodel.components.loss.dllm_loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/dllm_loss.md) - [nemo_automodel.components.loss.embedding_distill](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/embedding_distill.md) - [nemo_automodel.components.loss.infonce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/infonce.md) - [nemo_automodel.components.loss.intermediate_distill](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/intermediate_distill.md) - [nemo_automodel.components.loss.kd_loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/kd_loss.md) - [nemo_automodel.components.loss.linear_ce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/linear_ce.md) - [nemo_automodel.components.loss.linear_ce_base](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/linear_ce_base.md) - [nemo_automodel.components.loss.listmle](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/listmle.md) - [nemo_automodel.components.loss.loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/loss.md) - [nemo_automodel.components.loss.masked_ce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/masked_ce.md) - [nemo_automodel.components.loss.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/mtp.md) - [nemo_automodel.components.loss.soft_ce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/soft_ce.md) - [nemo_automodel.components.loss.te_parallel_ce](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/te_parallel_ce.md) - [nemo_automodel.components.loss.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/loss/utils.md) - [nemo_automodel.components.models](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models.md) - [nemo_automodel.components.models.bagel](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel.md) - [nemo_automodel.components.models.bagel.attention_masks](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/attention_masks.md) - [nemo_automodel.components.models.bagel.autoencoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/autoencoder.md) - [nemo_automodel.components.models.bagel.configuration](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/configuration.md) - [nemo_automodel.components.models.bagel.connector](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/connector.md) - [nemo_automodel.components.models.bagel.embeddings](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/embeddings.md) - [nemo_automodel.components.models.bagel.hf_backbone_loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/hf_backbone_loader.md) - [nemo_automodel.components.models.bagel.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/model.md) - [nemo_automodel.components.models.bagel.modeling_qwen2_packed](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/modeling_qwen2_packed.md) - [nemo_automodel.components.models.bagel.modeling_siglip_navit](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/modeling_siglip_navit.md) - [nemo_automodel.components.models.bagel.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/parallelization.md) - [nemo_automodel.components.models.bagel.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/bagel/state_dict_adapter.md) - [nemo_automodel.components.models.baichuan](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/baichuan.md) - [nemo_automodel.components.models.baichuan.configuration](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/baichuan/configuration.md) - [nemo_automodel.components.models.baichuan.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/baichuan/model.md) - [nemo_automodel.components.models.beam](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam.md) - [nemo_automodel.components.models.beam.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam/layers.md) - [nemo_automodel.components.models.beam.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam/model.md) - [nemo_automodel.components.models.beam.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam/parallelization.md) - [nemo_automodel.components.models.beam.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam/state_dict_adapter.md) - [nemo_automodel.components.models.beam.tokenization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/beam/tokenization.md) - [nemo_automodel.components.models.common](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common.md) - [nemo_automodel.components.models.common.bidirectional](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/bidirectional.md) - [nemo_automodel.components.models.common.cudnn_sparse_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/cudnn_sparse_attention.md) - [nemo_automodel.components.models.common.gated_delta_net_fp32](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/gated_delta_net_fp32.md) - [nemo_automodel.components.models.common.hf_checkpointing_mixin](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/hf_checkpointing_mixin.md) - [nemo_automodel.components.models.common.inbatch_neg_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/inbatch_neg_utils.md) - [nemo_automodel.components.models.common.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/mtp.md) - [nemo_automodel.components.models.common.mtp.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/mtp/mtp.md) - [nemo_automodel.components.models.common.packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/packing.md) - [nemo_automodel.components.models.common.rope_triton](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/rope_triton.md) - [nemo_automodel.components.models.common.tie_word_embeddings](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/tie_word_embeddings.md) - [nemo_automodel.components.models.common.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/common/utils.md) - [nemo_automodel.components.models.deepseek_v3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v3.md) - [nemo_automodel.components.models.deepseek_v3.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v3/layers.md) - [nemo_automodel.components.models.deepseek_v3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v3/model.md) - [nemo_automodel.components.models.deepseek_v3.rope_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v3/rope_utils.md) - [nemo_automodel.components.models.deepseek_v3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v3/state_dict_adapter.md) - [nemo_automodel.components.models.deepseek_v32](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v32.md) - [nemo_automodel.components.models.deepseek_v32.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v32/config.md) - [nemo_automodel.components.models.deepseek_v32.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v32/layers.md) - [nemo_automodel.components.models.deepseek_v32.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v32/model.md) - [nemo_automodel.components.models.deepseek_v32.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v32/state_dict_adapter.md) - [nemo_automodel.components.models.deepseek_v4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4.md) - [nemo_automodel.components.models.deepseek_v4.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/config.md) - [nemo_automodel.components.models.deepseek_v4.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/cp.md) - [nemo_automodel.components.models.deepseek_v4.dspark_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/dspark_target.md) - [nemo_automodel.components.models.deepseek_v4.flops](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/flops.md) - [nemo_automodel.components.models.deepseek_v4.fsdp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/fsdp.md) - [nemo_automodel.components.models.deepseek_v4.kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels.md) - [nemo_automodel.components.models.deepseek_v4.kernels.sparse_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/sparse_attention.md) - [nemo_automodel.components.models.deepseek_v4.kernels.tilelang_indexer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/tilelang_indexer.md) - [nemo_automodel.components.models.deepseek_v4.kernels.tilelang_indexer_bwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/tilelang_indexer_bwd.md) - [nemo_automodel.components.models.deepseek_v4.kernels.tilelang_indexer_fwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/tilelang_indexer_fwd.md) - [nemo_automodel.components.models.deepseek_v4.kernels.tilelang_sparse_mla_bwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/tilelang_sparse_mla_bwd.md) - [nemo_automodel.components.models.deepseek_v4.kernels.tilelang_sparse_mla_fwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/kernels/tilelang_sparse_mla_fwd.md) - [nemo_automodel.components.models.deepseek_v4.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/layers.md) - [nemo_automodel.components.models.deepseek_v4.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/model.md) - [nemo_automodel.components.models.deepseek_v4.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/mtp.md) - [nemo_automodel.components.models.deepseek_v4.optimized_kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/optimized_kernels.md) - [nemo_automodel.components.models.deepseek_v4.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/parallelization.md) - [nemo_automodel.components.models.deepseek_v4.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/processing.md) - [nemo_automodel.components.models.deepseek_v4.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/state_dict_adapter.md) - [nemo_automodel.components.models.deepseek_v4.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v4/vision.md) - [nemo_automodel.components.models.deepseek_v41](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41.md) - [nemo_automodel.components.models.deepseek_v41.attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/attention.md) - [nemo_automodel.components.models.deepseek_v41.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/config.md) - [nemo_automodel.components.models.deepseek_v41.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/cp.md) - [nemo_automodel.components.models.deepseek_v41.dspark](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/dspark.md) - [nemo_automodel.components.models.deepseek_v41.dspark_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/dspark_target.md) - [nemo_automodel.components.models.deepseek_v41.engram](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/engram.md) - [nemo_automodel.components.models.deepseek_v41.fsdp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/fsdp.md) - [nemo_automodel.components.models.deepseek_v41.indexer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/indexer.md) - [nemo_automodel.components.models.deepseek_v41.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/layers.md) - [nemo_automodel.components.models.deepseek_v41.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/model.md) - [nemo_automodel.components.models.deepseek_v41.packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/packing.md) - [nemo_automodel.components.models.deepseek_v41.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/processing.md) - [nemo_automodel.components.models.deepseek_v41.quantization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/quantization.md) - [nemo_automodel.components.models.deepseek_v41.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/state_dict_adapter.md) - [nemo_automodel.components.models.deepseek_v41.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deepseek_v41/vision.md) - [nemo_automodel.components.models.deprecation](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/deprecation.md) - [nemo_automodel.components.models.diffusion_gemma](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma.md) - [nemo_automodel.components.models.diffusion_gemma.attention_mask](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma/attention_mask.md) - [nemo_automodel.components.models.diffusion_gemma.fsdp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma/fsdp.md) - [nemo_automodel.components.models.diffusion_gemma.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma/layers.md) - [nemo_automodel.components.models.diffusion_gemma.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma/model.md) - [nemo_automodel.components.models.diffusion_gemma.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/diffusion_gemma/state_dict_adapter.md) - [nemo_automodel.components.models.ernie4_5](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ernie4_5.md) - [nemo_automodel.components.models.ernie4_5.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ernie4_5/model.md) - [nemo_automodel.components.models.ernie4_5.rope_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ernie4_5/rope_utils.md) - [nemo_automodel.components.models.ernie4_5.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ernie4_5/state_dict_adapter.md) - [nemo_automodel.components.models.flint](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint.md) - [nemo_automodel.components.models.flint.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/config.md) - [nemo_automodel.components.models.flint.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/layers.md) - [nemo_automodel.components.models.flint.magi](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/magi.md) - [nemo_automodel.components.models.flint.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/model.md) - [nemo_automodel.components.models.flint.packing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/packing.md) - [nemo_automodel.components.models.flint.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/parallelization.md) - [nemo_automodel.components.models.flint.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flint/state_dict_adapter.md) - [nemo_automodel.components.models.flux3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flux3.md) - [nemo_automodel.components.models.flux3.preprocessing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flux3/preprocessing.md) - [nemo_automodel.components.models.flux3.text_encoding](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flux3/text_encoding.md) - [nemo_automodel.components.models.flux3.types](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/flux3/types.md) - [nemo_automodel.components.models.gemma4_drafter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_drafter.md) - [nemo_automodel.components.models.gemma4_drafter.composite](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_drafter/composite.md) - [nemo_automodel.components.models.gemma4_drafter.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_drafter/model.md) - [nemo_automodel.components.models.gemma4_moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe.md) - [nemo_automodel.components.models.gemma4_moe.cp_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/cp_attention.md) - [nemo_automodel.components.models.gemma4_moe.cp_batch](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/cp_batch.md) - [nemo_automodel.components.models.gemma4_moe.cp_local_ring](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/cp_local_ring.md) - [nemo_automodel.components.models.gemma4_moe.loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/loss.md) - [nemo_automodel.components.models.gemma4_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/model.md) - [nemo_automodel.components.models.gemma4_moe.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/parallelization.md) - [nemo_automodel.components.models.gemma4_moe.sdpa_fp32](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/sdpa_fp32.md) - [nemo_automodel.components.models.gemma4_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_moe/state_dict_adapter.md) - [nemo_automodel.components.models.gemma4_unified](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_unified.md) - [nemo_automodel.components.models.gemma4_unified.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_unified/model.md) - [nemo_automodel.components.models.gemma4_unified.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gemma4_unified/state_dict_adapter.md) - [nemo_automodel.components.models.glm_moe_dsa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa.md) - [nemo_automodel.components.models.glm_moe_dsa.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/config.md) - [nemo_automodel.components.models.glm_moe_dsa.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/cp.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.cudnn_dsa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/cudnn_dsa.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.indexer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/indexer.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.sparse_mla](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/sparse_mla.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.tilelang_indexer_bwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/tilelang_indexer_bwd.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.tilelang_indexer_fwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/tilelang_indexer_fwd.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.tilelang_sparse_mla_bwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/tilelang_sparse_mla_bwd.md) - [nemo_automodel.components.models.glm_moe_dsa.kernels.tilelang_sparse_mla_fwd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/kernels/tilelang_sparse_mla_fwd.md) - [nemo_automodel.components.models.glm_moe_dsa.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/layers.md) - [nemo_automodel.components.models.glm_moe_dsa.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/model.md) - [nemo_automodel.components.models.glm_moe_dsa.optimized_kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/optimized_kernels.md) - [nemo_automodel.components.models.glm_moe_dsa.rope_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/rope_utils.md) - [nemo_automodel.components.models.glm_moe_dsa.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm_moe_dsa/state_dict_adapter.md) - [nemo_automodel.components.models.glm4_moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe.md) - [nemo_automodel.components.models.glm4_moe.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe/layers.md) - [nemo_automodel.components.models.glm4_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe/model.md) - [nemo_automodel.components.models.glm4_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe/state_dict_adapter.md) - [nemo_automodel.components.models.glm4_moe_lite](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe_lite.md) - [nemo_automodel.components.models.glm4_moe_lite.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm4_moe_lite/model.md) - [nemo_automodel.components.models.glm5_next](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next.md) - [nemo_automodel.components.models.glm5_next.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/config.md) - [nemo_automodel.components.models.glm5_next.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/cp.md) - [nemo_automodel.components.models.glm5_next.image_processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/image_processing.md) - [nemo_automodel.components.models.glm5_next.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/layers.md) - [nemo_automodel.components.models.glm5_next.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/model.md) - [nemo_automodel.components.models.glm5_next.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/processing.md) - [nemo_automodel.components.models.glm5_next.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/state_dict_adapter.md) - [nemo_automodel.components.models.glm5_next.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/glm5_next/vision.md) - [nemo_automodel.components.models.gpt_oss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt_oss.md) - [nemo_automodel.components.models.gpt_oss.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt_oss/layers.md) - [nemo_automodel.components.models.gpt_oss.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt_oss/model.md) - [nemo_automodel.components.models.gpt_oss.rope_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt_oss/rope_utils.md) - [nemo_automodel.components.models.gpt_oss.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt_oss/state_dict_adapter.md) - [nemo_automodel.components.models.gpt2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/gpt2.md) - [nemo_automodel.components.models.hunyuan_image3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3.md) - [nemo_automodel.components.models.hunyuan_image3.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/config.md) - [nemo_automodel.components.models.hunyuan_image3.flow_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/flow_adapter.md) - [nemo_automodel.components.models.hunyuan_image3.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/layers.md) - [nemo_automodel.components.models.hunyuan_image3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/model.md) - [nemo_automodel.components.models.hunyuan_image3.pipeline](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/pipeline.md) - [nemo_automodel.components.models.hunyuan_image3.release](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/release.md) - [nemo_automodel.components.models.hunyuan_image3.rope](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/rope.md) - [nemo_automodel.components.models.hunyuan_image3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hunyuan_image3/state_dict_adapter.md) - [nemo_automodel.components.models.hy_mt2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2.md) - [nemo_automodel.components.models.hy_mt2.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2/config.md) - [nemo_automodel.components.models.hy_mt2.dispatch](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2/dispatch.md) - [nemo_automodel.components.models.hy_mt2.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2/layers.md) - [nemo_automodel.components.models.hy_mt2.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2/model.md) - [nemo_automodel.components.models.hy_mt2.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_mt2/state_dict_adapter.md) - [nemo_automodel.components.models.hy_v3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_v3.md) - [nemo_automodel.components.models.hy_v3.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_v3/config.md) - [nemo_automodel.components.models.hy_v3.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_v3/layers.md) - [nemo_automodel.components.models.hy_v3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_v3/model.md) - [nemo_automodel.components.models.hy_v3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/hy_v3/state_dict_adapter.md) - [nemo_automodel.components.models.inkling](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling.md) - [nemo_automodel.components.models.inkling.configuration](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/configuration.md) - [nemo_automodel.components.models.inkling.feature_extraction](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/feature_extraction.md) - [nemo_automodel.components.models.inkling.image_processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/image_processing.md) - [nemo_automodel.components.models.inkling.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/layers.md) - [nemo_automodel.components.models.inkling.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/model.md) - [nemo_automodel.components.models.inkling.multimodal](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/multimodal.md) - [nemo_automodel.components.models.inkling.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/processing.md) - [nemo_automodel.components.models.inkling.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/state_dict_adapter.md) - [nemo_automodel.components.models.inkling.text](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/inkling/text.md) - [nemo_automodel.components.models.kimi_k2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k2.md) - [nemo_automodel.components.models.kimi_k2.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k2/config.md) - [nemo_automodel.components.models.kimi_k25_vl](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k25_vl.md) - [nemo_automodel.components.models.kimi_k25_vl.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k25_vl/model.md) - [nemo_automodel.components.models.kimi_k25_vl.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k25_vl/state_dict_adapter.md) - [nemo_automodel.components.models.kimi_k3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3.md) - [nemo_automodel.components.models.kimi_k3.attn_res_triton](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/attn_res_triton.md) - [nemo_automodel.components.models.kimi_k3.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/config.md) - [nemo_automodel.components.models.kimi_k3.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/cp.md) - [nemo_automodel.components.models.kimi_k3.encoding](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/encoding.md) - [nemo_automodel.components.models.kimi_k3.kda_fused](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/kda_fused.md) - [nemo_automodel.components.models.kimi_k3.kda_fused.chunk_kda_bwd_triton](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/kda_fused/chunk_kda_bwd_triton.md) - [nemo_automodel.components.models.kimi_k3.kda_fused.chunk_kda_fwd_cuda](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/kda_fused/chunk_kda_fwd_cuda.md) - [nemo_automodel.components.models.kimi_k3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/model.md) - [nemo_automodel.components.models.kimi_k3.multimodal](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/multimodal.md) - [nemo_automodel.components.models.kimi_k3.situ](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/situ.md) - [nemo_automodel.components.models.kimi_k3.situ_triton](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/situ_triton.md) - [nemo_automodel.components.models.kimi_k3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/state_dict_adapter.md) - [nemo_automodel.components.models.kimi_k3.tokenization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/tokenization.md) - [nemo_automodel.components.models.kimi_k3.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_k3/vision.md) - [nemo_automodel.components.models.kimi_linear](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_linear.md) - [nemo_automodel.components.models.kimi_linear.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_linear/config.md) - [nemo_automodel.components.models.kimi_linear.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_linear/cp.md) - [nemo_automodel.components.models.kimi_linear.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_linear/model.md) - [nemo_automodel.components.models.kimi_linear.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimi_linear/state_dict_adapter.md) - [nemo_automodel.components.models.kimivl](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimivl.md) - [nemo_automodel.components.models.kimivl.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/kimivl/model.md) - [nemo_automodel.components.models.laguna](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/laguna.md) - [nemo_automodel.components.models.laguna.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/laguna/config.md) - [nemo_automodel.components.models.laguna.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/laguna/model.md) - [nemo_automodel.components.models.laguna.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/laguna/state_dict_adapter.md) - [nemo_automodel.components.models.ling_v2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ling_v2.md) - [nemo_automodel.components.models.ling_v2.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ling_v2/config.md) - [nemo_automodel.components.models.ling_v2.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ling_v2/layers.md) - [nemo_automodel.components.models.ling_v2.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ling_v2/model.md) - [nemo_automodel.components.models.ling_v2.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ling_v2/state_dict_adapter.md) - [nemo_automodel.components.models.llama](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama.md) - [nemo_automodel.components.models.llama.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama/model.md) - [nemo_automodel.components.models.llama.rope_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama/rope_utils.md) - [nemo_automodel.components.models.llama_bidirectional](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_bidirectional.md) - [nemo_automodel.components.models.llama_bidirectional.export_onnx](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_bidirectional/export_onnx.md) - [nemo_automodel.components.models.llama_bidirectional.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_bidirectional/model.md) - [nemo_automodel.components.models.llama_nemotron_vl](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_nemotron_vl.md) - [nemo_automodel.components.models.llama_nemotron_vl.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_nemotron_vl/model.md) - [nemo_automodel.components.models.llama_nemotron_vl.processor](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llama_nemotron_vl/processor.md) - [nemo_automodel.components.models.llava_onevision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llava_onevision.md) - [nemo_automodel.components.models.llava_onevision.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llava_onevision/model.md) - [nemo_automodel.components.models.llava_onevision.rice_vit](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llava_onevision/rice_vit.md) - [nemo_automodel.components.models.llava_onevision.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/llava_onevision/state_dict_adapter.md) - [nemo_automodel.components.models.mimo_v2_flash](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash.md) - [nemo_automodel.components.models.mimo_v2_flash.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/config.md) - [nemo_automodel.components.models.mimo_v2_flash.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/cp.md) - [nemo_automodel.components.models.mimo_v2_flash.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/model.md) - [nemo_automodel.components.models.mimo_v2_flash.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/parallelization.md) - [nemo_automodel.components.models.mimo_v2_flash.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/processing.md) - [nemo_automodel.components.models.mimo_v2_flash.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/state_dict_adapter.md) - [nemo_automodel.components.models.mimo_v2_flash.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v2_flash/vision.md) - [nemo_automodel.components.models.mimo_v25](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v25.md) - [nemo_automodel.components.models.mimo_v25.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v25/config.md) - [nemo_automodel.components.models.mimo_v25.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v25/model.md) - [nemo_automodel.components.models.mimo_v25.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mimo_v25/state_dict_adapter.md) - [nemo_automodel.components.models.minimax_m2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m2.md) - [nemo_automodel.components.models.minimax_m2.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m2/layers.md) - [nemo_automodel.components.models.minimax_m2.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m2/model.md) - [nemo_automodel.components.models.minimax_m2.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m2/state_dict_adapter.md) - [nemo_automodel.components.models.minimax_m3_vl](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl.md) - [nemo_automodel.components.models.minimax_m3_vl.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/config.md) - [nemo_automodel.components.models.minimax_m3_vl.cp_sparse_attn](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/cp_sparse_attn.md) - [nemo_automodel.components.models.minimax_m3_vl.flops](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/flops.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels.msa_backward_postprocess_sm100](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels/msa_backward_postprocess_sm100.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels.msa_backward_preprocess_sm100](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels/msa_backward_preprocess_sm100.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels.msa_backward_sm100](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels/msa_backward_sm100.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels.msa_schedule](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels/msa_schedule.md) - [nemo_automodel.components.models.minimax_m3_vl.kernels.msa_task_build_sm100](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/kernels/msa_task_build_sm100.md) - [nemo_automodel.components.models.minimax_m3_vl.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/layers.md) - [nemo_automodel.components.models.minimax_m3_vl.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/model.md) - [nemo_automodel.components.models.minimax_m3_vl.msa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/msa.md) - [nemo_automodel.components.models.minimax_m3_vl.msa_bindings](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/msa_bindings.md) - [nemo_automodel.components.models.minimax_m3_vl.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/mtp.md) - [nemo_automodel.components.models.minimax_m3_vl.processing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/processing.md) - [nemo_automodel.components.models.minimax_m3_vl.recompute](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/recompute.md) - [nemo_automodel.components.models.minimax_m3_vl.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/state_dict_adapter.md) - [nemo_automodel.components.models.minimax_m3_vl.vision_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/minimax_m3_vl/vision_encoder.md) - [nemo_automodel.components.models.ministral_bidirectional](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ministral_bidirectional.md) - [nemo_automodel.components.models.ministral_bidirectional.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ministral_bidirectional/model.md) - [nemo_automodel.components.models.ministral_bidirectional.processor](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ministral_bidirectional/processor.md) - [nemo_automodel.components.models.ministral_bidirectional.reranker_export](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ministral_bidirectional/reranker_export.md) - [nemo_automodel.components.models.ministral_bidirectional.reranker_model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/ministral_bidirectional/reranker_model.md) - [nemo_automodel.components.models.mistral3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mistral3.md) - [nemo_automodel.components.models.mistral3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mistral3/model.md) - [nemo_automodel.components.models.mistral3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mistral3/state_dict_adapter.md) - [nemo_automodel.components.models.mistral3_vlm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/mistral3_vlm.md) - 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[nemo_automodel.components.models.nemotron_v3.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/nemotron_v3/state_dict_adapter.md) - [nemo_automodel.components.models.pixtral](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/pixtral.md) - [nemo_automodel.components.models.pixtral.compat](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/pixtral/compat.md) - [nemo_automodel.components.models.qwen_image_edit](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen_image_edit.md) - [nemo_automodel.components.models.qwen_image_edit.adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen_image_edit/adapter.md) - [nemo_automodel.components.models.qwen_image_edit.preprocessing](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen_image_edit/preprocessing.md) - [nemo_automodel.components.models.qwen2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen2.md) - [nemo_automodel.components.models.qwen2.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen2/model.md) - [nemo_automodel.components.models.qwen2_5_omni](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen2_5_omni.md) - [nemo_automodel.components.models.qwen2_5_omni.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen2_5_omni/model.md) - [nemo_automodel.components.models.qwen2_5_omni.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen2_5_omni/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3.md) - [nemo_automodel.components.models.qwen3.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3/model.md) - 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[nemo_automodel.components.models.qwen3_5_moe.cp_linear_attn](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_5_moe/cp_linear_attn.md) - [nemo_automodel.components.models.qwen3_5_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_5_moe/model.md) - [nemo_automodel.components.models.qwen3_5_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_5_moe/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3_8_flash_next](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next.md) - [nemo_automodel.components.models.qwen3_8_flash_next.backend](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/backend.md) - [nemo_automodel.components.models.qwen3_8_flash_next.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/config.md) - [nemo_automodel.components.models.qwen3_8_flash_next.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/cp.md) - [nemo_automodel.components.models.qwen3_8_flash_next.engram](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/engram.md) - [nemo_automodel.components.models.qwen3_8_flash_next.fa4_qsa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/fa4_qsa.md) - [nemo_automodel.components.models.qwen3_8_flash_next.flex_qsa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/flex_qsa.md) - [nemo_automodel.components.models.qwen3_8_flash_next.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/layers.md) - [nemo_automodel.components.models.qwen3_8_flash_next.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/model.md) - [nemo_automodel.components.models.qwen3_8_flash_next.qsa](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/qsa.md) - [nemo_automodel.components.models.qwen3_8_flash_next.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_8_flash_next/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3_moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_moe.md) - [nemo_automodel.components.models.qwen3_moe.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_moe/layers.md) - [nemo_automodel.components.models.qwen3_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_moe/model.md) - [nemo_automodel.components.models.qwen3_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_moe/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3_next](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_next.md) - [nemo_automodel.components.models.qwen3_next.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_next/layers.md) - [nemo_automodel.components.models.qwen3_next.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_next/model.md) - [nemo_automodel.components.models.qwen3_next.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_next/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3_omni_moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_omni_moe.md) - [nemo_automodel.components.models.qwen3_omni_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_omni_moe/model.md) - [nemo_automodel.components.models.qwen3_omni_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_omni_moe/state_dict_adapter.md) - [nemo_automodel.components.models.qwen3_reranker](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_reranker.md) - [nemo_automodel.components.models.qwen3_reranker.collator](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_reranker/collator.md) - [nemo_automodel.components.models.qwen3_reranker.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_reranker/model.md) - [nemo_automodel.components.models.qwen3_vl](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl.md) - [nemo_automodel.components.models.qwen3_vl.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl/model.md) - [nemo_automodel.components.models.qwen3_vl.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl/parallelization.md) - [nemo_automodel.components.models.qwen3_vl_moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl_moe.md) - [nemo_automodel.components.models.qwen3_vl_moe.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl_moe/model.md) - [nemo_automodel.components.models.qwen3_vl_moe.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/qwen3_vl_moe/state_dict_adapter.md) - [nemo_automodel.components.models.step3p5](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p5.md) - [nemo_automodel.components.models.step3p5.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p5/layers.md) - [nemo_automodel.components.models.step3p5.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p5/model.md) - [nemo_automodel.components.models.step3p5.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p5/state_dict_adapter.md) - [nemo_automodel.components.models.step3p7](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7.md) - [nemo_automodel.components.models.step3p7.configuration_step3p7](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/configuration_step3p7.md) - [nemo_automodel.components.models.step3p7.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/model.md) - [nemo_automodel.components.models.step3p7.mtp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/mtp.md) - [nemo_automodel.components.models.step3p7.processing_step3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/processing_step3.md) - [nemo_automodel.components.models.step3p7.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/state_dict_adapter.md) - [nemo_automodel.components.models.step3p7.vision_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step3p7/vision_encoder.md) - [nemo_automodel.components.models.step5](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5.md) - [nemo_automodel.components.models.step5.configuration](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/configuration.md) - [nemo_automodel.components.models.step5.cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/cp.md) - [nemo_automodel.components.models.step5.fa4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/fa4.md) - [nemo_automodel.components.models.step5.flops](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/flops.md) - [nemo_automodel.components.models.step5.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/layers.md) - [nemo_automodel.components.models.step5.model](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/model.md) - [nemo_automodel.components.models.step5.parallelization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/parallelization.md) - [nemo_automodel.components.models.step5.rope](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/rope.md) - [nemo_automodel.components.models.step5.sparse](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/sparse.md) - [nemo_automodel.components.models.step5.state_dict_adapter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/state_dict_adapter.md) - [nemo_automodel.components.models.step5.vision](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/models/step5/vision.md) - [nemo_automodel.components.moe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe.md) - [nemo_automodel.components.moe.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/config.md) - [nemo_automodel.components.moe.experts](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/experts.md) - [nemo_automodel.components.moe.fsdp_mixin](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/fsdp_mixin.md) - [nemo_automodel.components.moe.layers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/layers.md) - [nemo_automodel.components.moe.load_balance_metrics](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/load_balance_metrics.md) - [nemo_automodel.components.moe.megatron](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/megatron.md) - [nemo_automodel.components.moe.megatron.fused_a2a](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/megatron/fused_a2a.md) - [nemo_automodel.components.moe.megatron.fused_indices_converter](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/megatron/fused_indices_converter.md) - [nemo_automodel.components.moe.megatron.moe_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/megatron/moe_utils.md) - [nemo_automodel.components.moe.megatron.token_dispatcher](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/megatron/token_dispatcher.md) - [nemo_automodel.components.moe.mok_experts](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/mok_experts.md) - [nemo_automodel.components.moe.mxfp8](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/mxfp8.md) - [nemo_automodel.components.moe.optimized_ops](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/optimized_ops.md) - [nemo_automodel.components.moe.parallelizer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/parallelizer.md) - [nemo_automodel.components.moe.quantized_experts](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/quantized_experts.md) - [nemo_automodel.components.moe.router_replay](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/router_replay.md) - [nemo_automodel.components.moe.state_dict_mixin](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/state_dict_mixin.md) - [nemo_automodel.components.moe.state_dict_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/state_dict_utils.md) - [nemo_automodel.components.moe.swiglu_triton](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/swiglu_triton.md) - [nemo_automodel.components.moe.tp_plan_validation](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/tp_plan_validation.md) - [nemo_automodel.components.moe.uccl_ep](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/uccl_ep.md) - [nemo_automodel.components.moe.uccl_ep.buffer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/moe/uccl_ep/buffer.md) - [nemo_automodel.components.optim](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/optim.md) - [nemo_automodel.components.optim.dion](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/optim/dion.md) - [nemo_automodel.components.optim.optimizer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/optim/optimizer.md) - [nemo_automodel.components.optim.precision_warnings](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/optim/precision_warnings.md) - [nemo_automodel.components.optim.scheduler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/optim/scheduler.md) - [nemo_automodel.components.quantization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/quantization.md) - [nemo_automodel.components.quantization.fp8](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/quantization/fp8.md) - [nemo_automodel.components.quantization.mxfp4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/quantization/mxfp4.md) - [nemo_automodel.components.quantization.qat](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/quantization/qat.md) - [nemo_automodel.components.quantization.qlora](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/quantization/qlora.md) - [nemo_automodel.components.speculative](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative.md) - [nemo_automodel.components.speculative.bench_common](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/bench_common.md) - [nemo_automodel.components.speculative.bench_sglang](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/bench_sglang.md) - [nemo_automodel.components.speculative.bench_sweep](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/bench_sweep.md) - [nemo_automodel.components.speculative.bench_vllm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/bench_vllm.md) - [nemo_automodel.components.speculative.decode_eval](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/decode_eval.md) - [nemo_automodel.components.speculative.dflash](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash.md) - [nemo_automodel.components.speculative.dflash.core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/core.md) - [nemo_automodel.components.speculative.dflash.dflash2_core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/dflash2_core.md) - [nemo_automodel.components.speculative.dflash.domino_core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/domino_core.md) - [nemo_automodel.components.speculative.dflash.draft_kimi_k3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/draft_kimi_k3.md) - [nemo_automodel.components.speculative.dflash.draft_qwen3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/draft_qwen3.md) - [nemo_automodel.components.speculative.dflash.draft_qwen3_dflash2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/draft_qwen3_dflash2.md) - [nemo_automodel.components.speculative.dflash.jetspec_core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/jetspec_core.md) - [nemo_automodel.components.speculative.dflash.registry](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/registry.md) - [nemo_automodel.components.speculative.dflash.target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dflash/target.md) - [nemo_automodel.components.speculative.dspark](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark.md) - [nemo_automodel.components.speculative.dspark.common](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/common.md) - [nemo_automodel.components.speculative.dspark.config](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/config.md) - [nemo_automodel.components.speculative.dspark.core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/core.md) - [nemo_automodel.components.speculative.dspark.draft_deepseek_v4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_deepseek_v4.md) - [nemo_automodel.components.speculative.dspark.draft_gemma4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_gemma4.md) - [nemo_automodel.components.speculative.dspark.draft_glm_5_2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_glm_5_2.md) - [nemo_automodel.components.speculative.dspark.draft_kimi_k3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_kimi_k3.md) - [nemo_automodel.components.speculative.dspark.draft_minimax_m3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_minimax_m3.md) - [nemo_automodel.components.speculative.dspark.draft_qwen3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/draft_qwen3.md) - [nemo_automodel.components.speculative.dspark.loss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/loss.md) - [nemo_automodel.components.speculative.dspark.markov_head](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/markov_head.md) - [nemo_automodel.components.speculative.dspark.registry](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/registry.md) - [nemo_automodel.components.speculative.dspark.remote](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/remote.md) - [nemo_automodel.components.speculative.dspark.target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/target.md) - [nemo_automodel.components.speculative.dspark.target_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/dspark/target_utils.md) - [nemo_automodel.components.speculative.eagle](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle.md) - [nemo_automodel.components.speculative.eagle.backend](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/backend.md) - [nemo_automodel.components.speculative.eagle.core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/core.md) - [nemo_automodel.components.speculative.eagle.core_v12](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/core_v12.md) - [nemo_automodel.components.speculative.eagle.draft_deepseek](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_deepseek.md) - [nemo_automodel.components.speculative.eagle.draft_gemma](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_gemma.md) - [nemo_automodel.components.speculative.eagle.draft_gpt_oss](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_gpt_oss.md) - [nemo_automodel.components.speculative.eagle.draft_kimi_k3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_kimi_k3.md) - [nemo_automodel.components.speculative.eagle.draft_llama](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_llama.md) - [nemo_automodel.components.speculative.eagle.draft_llama_v12](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/draft_llama_v12.md) - [nemo_automodel.components.speculative.eagle.eagle4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/eagle4.md) - [nemo_automodel.components.speculative.eagle.export_eagle4](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/export_eagle4.md) - [nemo_automodel.components.speculative.eagle.msd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/msd.md) - [nemo_automodel.components.speculative.eagle.msd_curriculum](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/msd_curriculum.md) - [nemo_automodel.components.speculative.eagle.msd_decode](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/msd_decode.md) - [nemo_automodel.components.speculative.eagle.msd_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/msd_target.md) - [nemo_automodel.components.speculative.eagle.peagle_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/peagle_attention.md) - [nemo_automodel.components.speculative.eagle.peagle_data](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/peagle_data.md) - [nemo_automodel.components.speculative.eagle.peagle_draft](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/peagle_draft.md) - [nemo_automodel.components.speculative.eagle.peagle_trainer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/peagle_trainer.md) - [nemo_automodel.components.speculative.eagle.registry](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/registry.md) - [nemo_automodel.components.speculative.eagle.remote](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote.md) - [nemo_automodel.components.speculative.eagle.remote.client](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote/client.md) - [nemo_automodel.components.speculative.eagle.remote.protocol](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote/protocol.md) - [nemo_automodel.components.speculative.eagle.remote.server](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote/server.md) - [nemo_automodel.components.speculative.eagle.remote.transport](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote/transport.md) - [nemo_automodel.components.speculative.eagle.remote.wire](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/remote/wire.md) - [nemo_automodel.components.speculative.eagle.ring_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/ring_attention.md) - [nemo_automodel.components.speculative.eagle.sglang_runner](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/sglang_runner.md) - [nemo_automodel.components.speculative.eagle.sglang_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/sglang_target.md) - [nemo_automodel.components.speculative.eagle.target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/target.md) - [nemo_automodel.components.speculative.eagle.target_runner](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/target_runner.md) - [nemo_automodel.components.speculative.eagle.target_v12](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/target_v12.md) - [nemo_automodel.components.speculative.eagle.ulysses_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/ulysses_attention.md) - [nemo_automodel.components.speculative.eagle.vispec_core](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/vispec_core.md) - [nemo_automodel.components.speculative.eagle.vispec_draft](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/vispec_draft.md) - [nemo_automodel.components.speculative.eagle.vispec_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/vispec_target.md) - [nemo_automodel.components.speculative.eagle.vllm_runner](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/vllm_runner.md) - [nemo_automodel.components.speculative.eagle.vllm_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/vllm_target.md) - [nemo_automodel.components.speculative.eagle.zigzag_ring_attention](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/eagle/zigzag_ring_attention.md) - [nemo_automodel.components.speculative.precompute_dspark](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/precompute_dspark.md) - [nemo_automodel.components.speculative.precompute_eagle3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/precompute_eagle3.md) - [nemo_automodel.components.speculative.regen_loop](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/regen_loop.md) - [nemo_automodel.components.speculative.regenerate](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/regenerate.md) - [nemo_automodel.components.speculative.regenerate_vlm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/regenerate_vlm.md) - [nemo_automodel.components.speculative.serve_sglang](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/serve_sglang.md) - [nemo_automodel.components.speculative.serve_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/serve_target.md) - [nemo_automodel.components.speculative.serve_vllm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/serve_vllm.md) - [nemo_automodel.components.speculative.streaming](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming.md) - [nemo_automodel.components.speculative.streaming.async_pipeline](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/async_pipeline.md) - [nemo_automodel.components.speculative.streaming.eagle3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/eagle3.md) - [nemo_automodel.components.speculative.streaming.loader](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/loader.md) - [nemo_automodel.components.speculative.streaming.producer](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/producer.md) - [nemo_automodel.components.speculative.streaming.queue](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/queue.md) - [nemo_automodel.components.speculative.streaming.refs](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/refs.md) - [nemo_automodel.components.speculative.streaming.store](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/store.md) - [nemo_automodel.components.speculative.streaming.stores](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/stores.md) - [nemo_automodel.components.speculative.streaming.stores.local](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/stores/local.md) - [nemo_automodel.components.speculative.streaming.stores.shared_dir](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/streaming/stores/shared_dir.md) - [nemo_automodel.components.speculative.target_cp](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/speculative/target_cp.md) - [nemo_automodel.components.training](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training.md) - [nemo_automodel.components.training.domain_mixture](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/domain_mixture.md) - [nemo_automodel.components.training.ema](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/ema.md) - [nemo_automodel.components.training.embedding_row_repair](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/embedding_row_repair.md) - [nemo_automodel.components.training.garbage_collection](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/garbage_collection.md) - [nemo_automodel.components.training.model_output_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/model_output_utils.md) - [nemo_automodel.components.training.neftune](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/neftune.md) - [nemo_automodel.components.training.prewarm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/prewarm.md) - [nemo_automodel.components.training.rng](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/rng.md) - [nemo_automodel.components.training.signal_handler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/signal_handler.md) - [nemo_automodel.components.training.step_scheduler](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/step_scheduler.md) - [nemo_automodel.components.training.timers](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/timers.md) - [nemo_automodel.components.training.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/training/utils.md) - [nemo_automodel.components.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/utils.md) - [nemo_automodel.components.utils.compile_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/utils/compile_utils.md) - [nemo_automodel.components.utils.flops_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/utils/flops_utils.md) - [nemo_automodel.components.utils.model_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/utils/model_utils.md) - [nemo_automodel.components.utils.yaml_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/components/utils/yaml_utils.md) - [nemo_automodel.package_info](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/package_info.md) - [nemo_automodel.recipes](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes.md) - [nemo_automodel.recipes.base_recipe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/base_recipe.md) - [nemo_automodel.recipes.diffusion](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/diffusion.md) - [nemo_automodel.recipes.diffusion.train](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/diffusion/train.md) - [nemo_automodel.recipes.dllm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/dllm.md) - [nemo_automodel.recipes.dllm.strategy](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/dllm/strategy.md) - [nemo_automodel.recipes.dllm.train_ft](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/dllm/train_ft.md) - [nemo_automodel.recipes.kd_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/kd_utils.md) - [nemo_automodel.recipes.llm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm.md) - [nemo_automodel.recipes.llm.benchmark](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/benchmark.md) - [nemo_automodel.recipes.llm.kd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/kd.md) - [nemo_automodel.recipes.llm.peagle_recipe](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/peagle_recipe.md) - [nemo_automodel.recipes.llm.precompute_dspark_dist](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/precompute_dspark_dist.md) - [nemo_automodel.recipes.llm.serve_dspark_target](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/serve_dspark_target.md) - [nemo_automodel.recipes.llm.train_dflash](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_dflash.md) - [nemo_automodel.recipes.llm.train_dflash2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_dflash2.md) - [nemo_automodel.recipes.llm.train_domino](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_domino.md) - [nemo_automodel.recipes.llm.train_dspark](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_dspark.md) - [nemo_automodel.recipes.llm.train_eagle1](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_eagle1.md) - [nemo_automodel.recipes.llm.train_eagle2](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_eagle2.md) - [nemo_automodel.recipes.llm.train_eagle3](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_eagle3.md) - [nemo_automodel.recipes.llm.train_ft](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_ft.md) - [nemo_automodel.recipes.llm.train_jetspec](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_jetspec.md) - [nemo_automodel.recipes.llm.train_seq_cls](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_seq_cls.md) - [nemo_automodel.recipes.llm.train_vispec](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/llm/train_vispec.md) - [nemo_automodel.recipes.multimodal](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/multimodal.md) - [nemo_automodel.recipes.multimodal.finetune](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/multimodal/finetune.md) - [nemo_automodel.recipes.multimodal.pretrain](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/multimodal/pretrain.md) - [nemo_automodel.recipes.retrieval](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval.md) - [nemo_automodel.recipes.retrieval.distill_bi_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval/distill_bi_encoder.md) - [nemo_automodel.recipes.retrieval.mine_hard_negatives](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval/mine_hard_negatives.md) - [nemo_automodel.recipes.retrieval.mining_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval/mining_encoder.md) - [nemo_automodel.recipes.retrieval.train_bi_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval/train_bi_encoder.md) - [nemo_automodel.recipes.retrieval.train_cross_encoder](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/retrieval/train_cross_encoder.md) - [nemo_automodel.recipes.vlm](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/vlm.md) - [nemo_automodel.recipes.vlm.finetune](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/vlm/finetune.md) - [nemo_automodel.recipes.vlm.kd](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/recipes/vlm/kd.md) - [nemo_automodel.shared](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared.md) - [nemo_automodel.shared.embedding_padding](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/embedding_padding.md) - [nemo_automodel.shared.import_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/import_utils.md) - [nemo_automodel.shared.model_utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/model_utils.md) - [nemo_automodel.shared.parameter_names](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/parameter_names.md) - [nemo_automodel.shared.recompute_replay](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/recompute_replay.md) - [nemo_automodel.shared.retrieval_ids](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/retrieval_ids.md) - [nemo_automodel.shared.te_patches](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/te_patches.md) - [nemo_automodel.shared.tied_weights](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/tied_weights.md) - [nemo_automodel.shared.tokenizer_serialization](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/tokenizer_serialization.md) - [nemo_automodel.shared.torch_patches](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/torch_patches.md) - [nemo_automodel.shared.tp_linear](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/tp_linear.md) - [nemo_automodel.shared.transformers_patches](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/transformers_patches.md) - [nemo_automodel.shared.utils](https://docs.nvidia.com/nemo/automodel/v0.7/nemo-automodel/nemo_automodel/shared/utils.md) > **Note:** This page contains both a page directory (above) and the landing page content (below). The page directory is generated for agent use and does not appear on the landing page. > For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/v0.7/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server. # NeMo AutoModel Documentation > NeMo AutoModel is a PyTorch DTensor-native SPMD open source training library for scalable LLM and VLM training and fine-tuning with day-0 Hugging Face model support. PyTorch-native training that scales from 1 GPU to thousands with a single config change. Load any Hugging Face model, point at your data, and start training; no checkpoint conversion and no boilerplate. ## Documentation Map * [Get Started](/get-started/llms.txt): installation, configuration, Hugging Face compatibility, and repository structure. * [Training Recipes](/recipes-e2e-examples/overview): reusable training workflows and example configurations. * [Tutorials](/tutorials/overview): walkthroughs for specific models and tasks. * [Model Coverage](/model-coverage/llms.txt): supported architectures, model pages, and the model support log. * [Development](/development/llms.txt): parallelism, precision, checkpointing, and performance features. * [API Reference](/reference/llms.txt): generated Python API documentation. ๐Ÿค— HF Compatible ๐Ÿš€ Performance ๐Ÿ“ Scalability ๐ŸŽฏ SFT and PEFT ๐ŸŽจ Diffusion ๐Ÿ‘๏ธ VLM ๐ŸŒ Omni ๐ŸŒŠ dLLM ๐Ÿ”Š Audio โšก Speculative #### [About](/get-started/about) Overview of NeMo AutoModel and its capabilities. #### [Key Features](/get-started/key-features) Supported workflows, parallelism, recipes, and benchmarks. #### [๐Ÿค— HF Integration](/get-started/hf-compatibility) A `transformers`-compatible library with accelerated model implementations. #### [Model Coverage](/model-coverage/overview) Built on `transformers` for day-0 model support and OOTB compatibility. ## Get Started ```bash mkdir -p checkpoints docker run --gpus all -it --rm --shm-size=8g \ -v "$PWD/checkpoints:/opt/Automodel/checkpoints" \ nvcr.io/nvidia/nemo-automodel:26.10.00 \ automodel /opt/Automodel/examples/llm_finetune/qwen/qwen3_0p6b_hellaswag.yaml \ --nproc-per-node 2 \ --step_scheduler.max_steps 10 ``` This 10-step example fine-tunes [Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) on HellaSwag using two GPUs. The model and dataset are public; no Hugging Face token is required. Checkpoints are enabled and saved to the mounted `checkpoints` directory. See the [installation guide](/get-started/installation) for Docker prerequisites, source builds, and multi-node setup. See the [configuration guide](/get-started/configuration) for YAML recipes and CLI overrides. Launch on a [local workstation](/job-launchers/local-workstation) or [Slurm cluster](/job-launchers/slurm-cluster). ## 10 Most Recently Supported Models This short excerpt highlights the 10 newest additions. Pick a model below to start fine-tuning, or see the [full model support log](/model-coverage/release-log) for the complete history. ## Recipes and Guides Find the right guide for your task: fine-tuning, pretraining, distillation, diffusion, and more. | I want to... | Choose this when... | Input Data | Model | Guide | | ------------------------------- | ------------------------------------------------------------------------------------------------- | ------------------------------------------------- | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **SFT (full fine-tune)** | You need maximum accuracy and have the GPU budget to update all weights | Instruction / chat dataset | LLM | [Start fine-tuning](/recipes-e2e-examples/sft-peft) | | **PEFT (LoRA)** | You want to fine-tune on limited GPU memory; updates \<1% of parameters | Instruction / chat dataset | LLM | [Start LoRA](/recipes-e2e-examples/sft-peft) | | **Tool / function calling** | Your model needs to call APIs or tools with structured arguments | Function-calling dataset (queries + tool schemas) | LLM | [Add tool calling](/recipes-e2e-examples/function-calling) | | **Fine-tune VLM** | Your task involves both images and text (e.g., visual QA, captioning) | Image + text dataset | VLM | [Fine-tune VLM](/recipes-e2e-examples/gemma-3-3n) | | **Fine-tune Gemma 4** | You want to fine-tune Gemma 4 for structured extraction from images (e.g., receipts) | Image + text dataset | VLM | [Fine-tune Gemma 4](/recipes-e2e-examples/gemma-4) | | **Fine-tune dLLM** | You want to fine-tune a diffusion language model (e.g., LLaDA) using masked denoising | Instruction / chat dataset | dLLM | [Fine-tune dLLM](/recipes-e2e-examples/dllm-fine-tuning) | | **Fine-tune Diffusion** | You want to fine-tune a diffusion model for image or video generation | Video / Image dataset | Diffusion | [Fine-tune Diffusion](/recipes-e2e-examples/diffusion-fine-tuning) | | **Fine-tune VLM-MoE** | You need large-scale vision-language training with sparse MoE efficiency | Image + text dataset | VLM (MoE) | [Fine-tune VLM-MoE](/recipes-e2e-examples/qwen3-5-vl) | | **Fine-tune agentic VLM-MoE** | You need image/video context for agentic developer workflows | Image / video + text dataset | VLM (MoE) | [Fine-tune Step-3.7-Flash](/recipes-e2e-examples/step-3-7) | | **Fine-tune Audio ASR** | Adapt Qwen3-Omni for speech recognition on HF audio datasets | Audio + transcript dataset | Qwen3-Omni | [Fine-tune Qwen3-Omni ASR](/recipes-e2e-examples/qwen3-omni-asr) | | **Embedding fine-tune** | You want to improve text similarity for search, retrieval, or RAG | Text pairs / retrieval corpus | LLM | [Train a bi-encoder or cross-encoder](/recipes-e2e-examples/retrieval-finetune), [Nemotron end-to-end text bi-encoder recipe](https://github.com/NVIDIA-NeMo/Nemotron/tree/main/docs/nemotron/embed) | | **Fine-tune a large MoE** | You are adapting a large sparse MoE model (DeepSeek-V3, GLM-5, etc.) to your domain | Text dataset (e.g., HellaSwag) | LLM (MoE) | [Fine-tune MoE](/recipes-e2e-examples/large-moe-fine-tuning) | | **Fine-tune DeepSeek-V4 Flash** | You want to fine-tune the DeepSeek-V4 Flash hybrid-attention MoE (SWA / CSA / HCA + hash-routing) | Text dataset (e.g., HellaSwag) | LLM (MoE) | [Fine-tune DeepSeek-V4 Flash](/recipes-e2e-examples/deepseek-v4-flash) | | **Fine-tune Hy3-preview** | You want to fine-tune Tencent's 295B MoE with sigmoid routing and per-head QK RMSNorm | Text dataset (e.g., HellaSwag) | LLM (MoE) | [Fine-tune Hy3-preview](/recipes-e2e-examples/hy3-preview) | | **Fine-tune Nemotron-3 Ultra** | You want to fine-tune NVIDIA's 550B-A55B hybrid Mamba-2 / LatentMoE model with MTP | Text dataset (e.g., HellaSwag) | LLM (MoE) | [Fine-tune Nemotron-3 Ultra](/recipes-e2e-examples/nemotron-3-ultra) | | **Sequence classification** | You need to classify text into categories (sentiment, topic, NLI) | Text + labels (e.g., GLUE MRPC) | LLM | [Train classifier](/recipes-e2e-examples/sequence-classification) | | **QAT fine-tune** | You want a quantized model that keeps accuracy for efficient deployment | Text dataset | LLM | [Enable QAT](/recipes-e2e-examples/qat) | | **Knowledge distillation** | You want a smaller, faster model that retains most of the teacher's quality | Instruction dataset + teacher model | LLM | [Distill a model](/recipes-e2e-examples/knowledge-distillation) | | **Pretrain an LLM** | You are building a base model from scratch on your own corpus | Large unlabeled text corpus (e.g., FineWeb-Edu) | LLM | [Start pretraining](/recipes-e2e-examples/pretraining) | | **Pretrain (NanoGPT)** | You want quick pretraining experiments on a single node | FineWeb / text corpus | LLM | [Try NanoGPT](/recipes-e2e-examples/nanogpt-pretraining) | ## Performance Recent BF16 full fine-tuning results on NVIDIA H100 80GB GPUs, using the workloads and sequence lengths below. | Model | GPUs | Workload | Sequence Length | Tokens/sec/GPU | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---: | ------------- | --------------: | -------------: | | [Qwen3.8-27B](https://github.com/NVIDIA-NeMo/Automodel/blob/b203f3f9f9f3140c660942a088ff36bbc3a5e856/examples/vlm_finetune/qwen3_8/qwen3_8_27b.yaml) | 8 | MedPix VLM | Variable | 233.07 | | [GLM-5.3](https://github.com/NVIDIA-NeMo/Automodel/blob/b203f3f9f9f3140c660942a088ff36bbc3a5e856/examples/llm_finetune/glm/glm_5.3_tulu3_4k_cudnn_100step.yaml) | 256 | Tulu-3 packed | 4096 | 162.56 | | [MiMo-V2.6-Flash-RL](https://github.com/NVIDIA-NeMo/Automodel/blob/b203f3f9f9f3140c660942a088ff36bbc3a5e856/examples/llm_finetune/mimo_v2_flash/mimo_v2_6_flash_rl_tulu3_packed4k_ep64_cp2_100steps.yaml) | 64 | Tulu-3 packed | 4096 | 640.80 | | [Nemotron-3.5-Lightning-30B-A3B-BF16](https://github.com/NVIDIA-NeMo/Automodel/blob/b203f3f9f9f3140c660942a088ff36bbc3a5e856/examples/llm_finetune/nemotron/nemotron_nano_v3_5_lightning_tulu3_packed_cp8_64k.yaml) | 8 | Tulu-3 packed | 8192 | 6,895.85 | Qwen3.8-27B freezes the vision encoder. See the [full benchmark results](/performance/performance-summary) for measurement settings, pinned recipes, and more models. ## Advanced Topics Parallelism, precision, checkpointing strategies, and experiment tracking. #### [Pipeline Parallelism](/development/pipeline-parallelism) Torch-native pipelining composable with FSDP2 and DTensor. 3d-parallelism #### [FP8 Training](/development/fp8-training) Mixed-precision FP8 training with torchao. FP8 mixed-precision #### [Mixed-Precision Training](/development/mixed-precision-training) FP32 master weights, BF16 compute, and the precision traps to avoid. BF16 mixed-precision #### [Checkpointing](/development/checkpointing) Distributed checkpoints with SafeTensors output. DCP safetensors #### [Gradient Checkpointing](/development/gradient-checkpointing) Trade compute for memory with activation checkpointing. memory-efficiency #### [Quantization-Aware Training](/recipes-e2e-examples/qat) Train with quantization for deployment-ready models. QAT #### [Experiment Tracking](/development/mlflow-logging) Track experiments and metrics with MLflow and W\&B. MLflow Wandb ## For Developers #### [Repo Internals](/get-started/repo-structure) Components, recipes, and CLI architecture. #### [API Reference](/reference/api-reference) Auto-generated Python API documentation. #### [Use as a Library](/get-started/about) Drop-in accelerated backend for TRL, lm-eval-harness, OpenRLHF, or any code that loads Hugging Face models. --- :: :: :: :: :: :: :: ::