The Hugging Face Integration
The Hugging Face Hub 🤗 is a central place where anyone can share and download models.
It allows you to: - Host your trained models. - Download trained models from the community. - Visualize your agents playing directly on your browser.
You can see the list of ml-agents models here.
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
- A short tutorial where you teach Huggy the Dog to fetch the stick and then play with him directly in your browser
- A more in-depth tutorial
Download a model from the Hub
You can simply download a model from the Hub using mlagents-load-from-hf
.
You need to define two parameters:
--repo-id
: the name of the Hugging Face repo you want to download.--local-dir
: the path to download the model.
For instance, I want to load the model with model-id "ThomasSimonini/MLAgents-Pyramids" and put it in the downloads directory:
mlagents-load-from-hf --repo-id="ThomasSimonini/MLAgents-Pyramids" --local-dir="./downloads"
Upload a model to the Hub
You can simply upload a model to the Hub using mlagents-push-to-hf
You need to define four parameters:
--run-id
: the name of the training run id.--local-dir
: where the model was saved--repo-id
: the name of the Hugging Face repo you want to create or update. It’s always/ If the repo does not exist it will be created automatically --commit-message
: since HF repos are git repositories you need to give a commit message.
For instance, I want to upload my model trained with run-id "SnowballTarget1" to the repo-id: ThomasSimonini/ppo-SnowballTarget:
mlagents-push-to-hf --run-id="SnowballTarget1" --local-dir="./results/SnowballTarget1" --repo-id="ThomasSimonini/ppo-SnowballTarget" --commit-message="First Push"
Visualize an agent playing
You can watch your agent playing directly in your browser (if the environment is from the ML-Agents official environments)
- Step 1: Go to https://huggingface.co/unity and select the environment demo.
- Step 2: Find your model_id in the list.
- Step 3: Select your .nn /.onnx file.
- Step 4: Click on Watch the agent play