Install NeMo Automodel#

This guide explains how to install NeMo Automodel for LLM, VLM, and OMNI models on various platforms and environments. Depending on your use case, there are several ways to install it:

Method

Dev Mode

Use Case

Recommended For

📦 PyPI

-

Install stable release with minimal setup

Most users, production usage

🐳 Docker

-

Use in isolated GPU environments, e.g., with NeMo container

Multinode deployments

🐍 Git Repo

✅

Use the latest code without cloning or installing extras manually

Power users, testers

🧪 Editable Install

✅

Contribute to the codebase or make local modifications

Contributors, researchers

🐳 Docker + Mount

✅

Use in isolated GPU environments, e.g., with NeMo container

Multinode deployments

Prerequisites#

System Requirements#

  • Python: 3.9 or higher

  • CUDA: 11.8 or higher (for GPU support)

  • Memory: Minimum 16GB RAM, 32GB+ recommended

  • Storage: At least 50GB free space for models and datasets

Hardware Requirements#

  • GPU: NVIDIA GPU with 8GB+ VRAM (16GB+ recommended)

  • CPU: Multi-core processor (8+ cores recommended)

  • Network: Stable internet connection for downloading models

Installation Options for Non-Developers#

This section explains the easiest installation options for non-developers, including using pip3 via PyPI or leveraging a preconfigured NVIDIA NeMo Docker container. Both methods offer quick access to the latest stable release of NeMo Automodel with all required dependencies.

Install via NeMo Docker Container#

You can use NeMo Automodel with the NeMo Docker container. Pull the container by running:

docker pull nvcr.io/nvidia/nemo:25.07

Note

The above docker command uses the 25.07 container. Use the most recent container version to ensure you get the latest version of Automodel and its dependencies like torch, transformers, etc.

Then you can enter the container using:

docker run --gpus all -it --rm \
  --shm-size=8g \
  nvcr.io/nvidia/nemo:25.07

Installation Options for Developers#

This section provides installation options for developers, including pulling the latest source from GitHub, using editable mode, or mounting the repo inside a NeMo Docker container.

Install via GitHub (Source)#

If you want the latest features from the main branch or want to contribute:

Option A - Use pip with git repo:#

pip3 install git+https://github.com/NVIDIA-NeMo/Automodel.git

Note

This installs the repo as a standard Python package (not editable).

Option B - Use uv with git repo:#

uv pip install git+https://github.com/NVIDIA-NeMo/Automodel.git

Note

uv handles virtual environment transparently and enables more reproducible installs.

Install in Developer Mode (Editable Install)#

To contribute or modify the code:

git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel
pip3 install -e .

Note

This installs Automodel in editable mode, so changes to the code are immediately reflected in Python.

Mount the Repo into a NeMo Docker Container#

To run Automodel inside a NeMo container while mounting your local repo, follow these steps:

# Step 1: Clone the Automodel repository.
git clone https://github.com/NVIDIA-NeMo/Automodel.git && cd Automodel && \

# Step 2: Pull the latest compatible NeMo container (replace 25.07 with latest if needed).
docker pull nvcr.io/nvidia/nemo:25.07 && \

# Step 3: Run the NeMo container with GPU support, shared memory, and mount the repo.
docker run --gpus all -it --rm \
  -v $(pwd):/workspace/Automodel \         # Mount repo into container workspace
  -v $(pwd)/Automodel:/opt/Automodel \     # Optional: Mount Automodel under /opt for flexibility
  --shm-size=8g \                           # Increase shared memory for PyTorch/data loading
  nvcr.io/nvidia/nemo:25.07 /bin/bash -c "\
    cd /workspace/Automodel && \           # Enter the mounted repo
    pip install -e . && \                  # Install Automodel in editable mode
    python3 examples/llm/finetune.py" # Run a usage example

Note

The above docker command uses the volume -v option to mount the local Automodel directory under /opt/Automodel.

Bonus: Install Extras#

Some functionality may require optional extras. You can install them like this:

pip3 install nemo-Automodel[cli]    # Installs only the Automodel CLI
pip3 install nemo-Automodel         # Installs the CLI and all LLM dependencies.
pip3 install nemo-Automodel[vlm]    # Install all VLM-related dependencies.

Summary#

Goal

Command or Method

Stable install (PyPI)

pip3 install nemo-automodel

Latest from GitHub

pip3 install git+https://github.com/NVIDIA-NeMo/Automodel.git

Editable install (dev mode)

pip install -e . after cloning

Run without installing

Use PYTHONPATH=$(pwd) to run scripts

Use in Docker container

Mount repo and pip install -e . inside container

Fast install (via uv)

uv pip install ...