> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# Recipes & E2E Examples

## Docs

- [Recipes and End-to-End Examples](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/overview.md): 
- [Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/sft-peft.md): 
- [Function Calling with NeMo AutoModel using FunctionGemma](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/function-calling.md): 
- [Knowledge Distillation with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/knowledge-distillation.md): 
- [Fine-Tune Large MoE LLMs](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/large-moe-fine-tuning.md): 
- [DeepSeek V4 Flash](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/deepseek-v4-flash.md): 
- [Hy3-preview](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/hy3-preview.md): 
- [Pretraining Megatron Core Datasets with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/pretraining.md): 
- [LLM Pre-Training with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/nanogpt-pretraining.md): 
- [Sequence Classification (SFT/PEFT) with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/sequence-classification.md): 
- [Fine-Tune Gemma 3 and Gemma 3n](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/gemma-3-3n.md): 
- [Fine-Tuning Gemma 4 31B on CORD-v2 Receipts — End-to-End Guide](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/gemma-4.md): 
- [Fine-Tune Qwen3.5-VL](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/qwen3-5-vl.md): 
- [Nemotron-Omni](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/nemotron-omni.md): 
- [Mistral Medium 3.5 VL](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/mistral-medium-3-5.md): 
- [Diffusion Model Fine-Tuning with NeMo AutoModel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/diffusion-fine-tuning.md): 
- [dLLM Fine-Tuning](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/dllm-fine-tuning.md): 
- [Quantization-Aware Training (QAT) in NeMo Automodel](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/qat.md): 
- [Model Training on Databricks](https://docs.nvidia.com/nemo/automodel/v0.4/recipes-e2e-examples/databricks.md):