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ai-agent

Automodel: Train LLMs Faster

Train large language models with Pytorch native distributed support. For founders needing AI acceleration.
intermediateโฑ 1-2 hours๐Ÿ’ต Free
747 stars224 forksPythonQuality 8/10Updated 7/21/2026100% free ยท open source
What it is

Trains large language models using NVIDIA's PyTorch and Hugging Face technology.

What you can make with it

LLMs (Language Models) like those fine-tuned with GPT-3, or a custom Virtual Language Model.

How it helps

This skill saves you time and cost by using PyTorch and Hugging Face, and letting you fine-tune LLMs on demand, without needing to know how to handle large model training from scratch.

Real use case example

"A solo developer, Alex, wants to create a chat interface on their website. They write a script to fine-tune a pre-trained LLM with GPT-3 using this skill, then integrate the model into their site using NVIDIA's PyTorch and Hugging Face. After a few hours of work, Alex has a functioning chat interface that understands their users' queries."

If you're new

Beginners should learn this when they start experimenting with building their first chat-based interface.

If you're senior

Senior developers and researchers will find this tool useful when building and fine-tuning large language models for complex applications.

Common confusion cleared up

This skill does not come with pre-trained models; users must fine-tune their own LLMs using pre-trained models or their own custom data.

Best inside these AI tools
Claude Desktop
Pairs with
Claude APIStripe webhookNotion database
Why we list it on WorkflowStacks: This skill is free and open-source, making it a valuable addition to a marketplace of AI tools, as it can be used without committing to a paid plan or vendor.
What it does

Automodel allows founders to train large language models using Pytorch's native distributed support, accelerating AI development with out-of-the-box Hugging Face support.

Install / run
pip install automodel
When to use it
  • โ€ขWhen you need to train large language models quickly and efficiently
  • โ€ขWhen you want to leverage Pytorch's native distributed support for scaling your AI models
  • โ€ขWhen you're working with Hugging Face models and want a streamlined training process
Quick start
  1. 1Clone the Automodel repository using `git clone https://github.com/NVIDIA-NeMo/Automodel.git`
  2. 2Navigate to the repository directory with `cd Automodel`
  3. 3Run `python setup.py install` to install the package
  4. 4Use the `automodel` command to start training a model, referencing the example config in `configs/example_config.json`
  5. 5Modify the `example_config.json` file to suit your specific model training needs
Ready-to-paste prompt
python automodel/train.py --config configs/example_config.json --model_name my_large_language_model
Heads up: Ensure you have the correct version of Pytorch installed, as Automodel relies on Pytorch's native distributed support, and incompatible versions may cause issues
Saves to your device

Topics

agent
deepseek-v3-2
deepseek-v4
finetuning
gemma3
gemma4
glm
gpt-oss
kimi-k2
llama
llama3
llm
minimax-m2
mistral
openai
qwen3
qwen3-6
qwen3-next
vlm
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

16
top-level files
12
folders
66.7M
repo size
Apache-2.0
license
Key files
.pre-commit-config.yaml
AGENTS.md
README.md
File tree
.agents/
.claude/
.github/
docker/
docs/
examples/
nemo_automodel/
scripts/
skills/
tests/
tools/
tutorials/
.flake8
.gitignore
.pre-commit-config.yaml
.pylintrc
.python-version
AGENTS.md
app.py
CLAUDE.md
codecov.yml
CONTRIBUTING.md
LICENSE
pyproject.toml
Quick Actions
Details
Creator
NVIDIA-NeMo
Language
Python
Category
ai-agent
Published
5/21/2025

Are you the creator of this tool? Claim your listing โ†’ and earn 85% of every sale.

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