NeMo AutoModel

NeMo AutoModel is a worfkow within the NeMo machine learning framework that supports both pretraining and fine-tuning Large Language Models (LLMs), designed to accelerate your journey from data to deployment. Whether you’re a researcher or a developer, NeMo AutoModel makes it incredibly easy to fine-tune state-of-the-art models from Hugging Face with minimal setup. You’ll benefit from:

• Day-0 Support: Models available on Hugging Face Hub can be fine-tuned instantly on your own custom dataset.

• Seamless Hugging Face Integration: Models fine-tuned with NeMo AutoModel are fully compatible with the Hugging Face ecosystem.

• Rapid Experimentation: Start experimenting in minutes using ready-made scripts, notebooks, and run recipes.

• Distributed Fine-Tuning: Scale your fine-tuning with Fully Sharded Data Parallelism 2 (FSDP2).

• Accelerated Iteration: Enables rapid experimentation by streamlining model fine-tuning, evaluation, and deployment, so you can iterate faster on your research and applications.

Quickstart

Ready to start? Here are the best resources to dive in:

• For Parameter-Efficient Fine-Tuning (PEFT):

  • Read the PEFT User Guide automodel/peft.rst.

  • Try the Quickstart using the standalone python3 PEFT script.

  • Follow the guided Jupyter Notebook.

  • Access the NeMo-Run recipe.

• For Supervised Fine-Tuning (SFT):

  • Consult the SFT User Guide automodel/sft.rst.

  • Run the standalone python3 SFT script.

  • Explore the Jupyter Notebook.

  • Check out the Multinode Jupyter Notebook.

  • See the NeMo-Run recipe.

Start exploring today and unlock the power of your LLMs!

Known Issues

• NeMo AutoModel is currently in preview release; limitations are expected in performance and memory usage.