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NeMo-AutoModel

GitHub

NeMo-AutoModel

GitHub

Table of Contents

Get Started

About NeMo AutoModel
Key Features and Concepts
Install NeMo AutoModel
YAML Configuration
🤗 Transformers API Compatibility
Run on Your Local Workstation
Run on a Cluster
Repository Structure

Announcements

Announcements

NeMo AutoModel Performance

Performance Summary

Model Coverage

Model Coverage Overview
Large Language Models (LLMs)
Vision Language Models (VLMs)
Troubleshooting Unsupported Models

Recipes & E2E Examples

Recipes and End-to-End Examples
Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) with NeMo Automodel
Function Calling with NeMo Automodel using FunctionGemma
Knowledge Distillation with NeMo-AutoModel
Pretraining using Megatron Core Datasets with NeMo Automodel
LLM Pre-Training with NeMo Automodel
Sequence Classification (SFT/PEFT) with NeMo Automodel
Fine-Tune Gemma 3 and Gemma 3n
Fine-Tune Qwen3.5-VL
Quantization-Aware Training (QAT) in NeMo Automodel
Model Training on Databricks

Datasets

Dataset Overview: LLM, VLM, and Retrieval Datasets in NeMo Automodel
Integrate Your Own Text Dataset
Biencoder Retrieval Dataset (Embedding Fine-tuning)
Use the ColumnMappedTextInstructionDataset
Use the ColumnMappedTextInstructionIterableDataset (Streaming)
Integrate Your Own Multi-Modal Dataset

Development

Checkpointing in NeMo Automodel
🚀 Gradient (Activation) Checkpointing in NeMo-AutoModel
Pipeline Parallelism with AutoPipeline
FP8 Training in NeMo Automodel
MLflow Logging in NeMo Automodel
API Reference
- nemo_automodel

API Reference
nemo_automodel
nemo_automodel.components
nemo_automodel.components.attention

`nemo_automodel.components.attention`#

Submodules#

nemo_automodel.components.attention.utils
nemo_automodel.components.attention.flex_attention

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Last updated on 2026-03-01.