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You are viewing the NeMo 2.0 documentation. This release introduces significant changes to the API and a new library, NeMo Run. We are currently porting all features from NeMo 1.0 to 2.0. For documentation on previous versions or features not yet available in 2.0, please refer to the NeMo 24.07 documentation.

NVIDIA NeMo Framework User Guide

Table of Contents

NeMo Framework

Overview
Install NeMo Framework
Performance
Why NeMo Framework?

Getting Started

Quickstart with NeMo-Run
Quickstart with NeMo 2.0 API
Tutorials

Developer Guides

Migration Guide
Feature Guide
Best Practices

Training and Customization

Long Context Training
- Context Parallelism
Optimal Configuration with Auto Configurator
Parameter-Efficient Fine-tuning (PEFT)
- Supported PEFT Methods
- A Comparison of Performant and Canonical LoRA Variants
Sequence Packing
Resiliency
Continual Training
Custom Datasets
- Pre-Training Data Module
- Fine-Tuning Data Module

NeMo AutoModel

Overview
Parameter-Efficient Fine-tuning (PEFT)
Supervised Fine-tuning (SFT)
Vision Language Models with NeMo AutoModel

Model Optimization

Quantization
Pruning
Distillation

Models

Large Language Models
- Baichuan 2
- ChatGLM 3
- DeepSeek V2
- DeepSeek V3
- Gemma
- Gemma 2
- Hyena
- Llama 3
- Mamba 2
- Mixtral
- Nemotron
- Phi 3
- Qwen2/2.5
- Starcoder
- Starcoder 2
- T5
- BERT
Vision Language Models
Speech AI Models
Diffusion Models
- Flux
- Diffusion Training Framework
Embedding Models
- SBERT
- Llama Embedding

Deploy Models

Overview
Large Language Models
Multimodal Models

Library Documentation

Overview
NeMo
NeMo Aligner
NeMo Curator
NeMo Run

Releases

Software Component Versions
Changelog
Known Issues

Data Curation
API Reference
LLM Services

LLM Services#

Last updated on Apr 18, 2025.