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NeMo-AutoModel

GitHub

NeMo-AutoModel

GitHub

Table of Contents

Get Started

Introduction to the NeMo Automodel Repository
Install NeMo Automodel
Run on Your Local Workstation

Announcements

Challenges in Enabling PyTorch Native Pipeline Parallelism for Hugging Face Transformer Models
Google Gemma 3n: Efficient Multimodal Fine-tuning Made Simple
Fine-tune Hugging Face Models Instantly with Day-0 Support with NVIDIA NeMo AutoModel

E2E Examples

Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) with NeMo Automodel
Pretraining using Megatron-Core Datasets with NeMo Automodel
LLM Pre-Training with NeMo AutoModel
Fine-Tune Gemma 3 and Gemma 3n

Model Coverage

Large Language Models (LLMs)
Vision Language Models (VLMs)

Datasets

Dataset Overview: LLM and VLM Datasets in NeMo Automodel
Integrate Your Own Text Dataset
Use the ColumnMappedTextInstructionDataset
Integrate Your Own Multi-Modal Dataset

Development

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

Performance

NeMo AutoModel Performance Summary

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