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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 AutoModel 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)
Diffusion Models
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
Fine-Tune Large MoE LLMs
Pretraining 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
Diffusion Model Fine-Tuning with NeMo AutoModel
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
Diffusion Dataset Preparation

Job Launchers

Run on Any Cloud with SkyPilot

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.models
nemo_automodel.components.models.baichuan

`nemo_automodel.components.models.baichuan`#

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Last updated on 2026-03-27.