The Hugging Face Hub 🤗 is now officially integrated in the ML-Agents official repository.

The documentation 👉 https://huggingface.co/docs/hub/ml-agents

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Unity ML-Agents Toolkit with Hugging Face 🤗

This is a Fork of the Unity ML-Agents toolkit. This version allows you to publish your trained agents in one line of code to the Hugging Face Hub, download powerful agents from the community, and watch a replay of your agent without using the Unity Editor.

⚠️ This is an experimental version, that might be subject to change. If you encounter some issues, please open an issue. Don't forget to check what environments are currently available.

Getting started

➡️ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub 👉 https://link.medium.com/KOpvPdyz4qb

Step 1: Install the package

# Clone the repository
git clone https://github.com/huggingface/ml-agents/

# Go inside the repository and install the package
cd ml-agents
pip3 install -e ./ml-agents-envs
pip3 install -e ./ml-agents

Step 2: Download the Environment Executable

⚠️ For now, we have only the Pyramids, Worm, Walker, and Push Block windows exe, but we’re going to publish Linux and Mac versions too.

In the meantime, if you have a Mac or a Linux, you can replace step 2 with: https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Learning-Environment-Executable.md#building-the-3dball-environment

Download executable zip from here: https://drive.google.com/drive/folders/1HrvHNRLCKwQRWv-JkhhMPTHCwu_iHxZj?usp=sharing

Unzip it and place it inside the MLAgents cloned repo in a new folder called trained-envs-executables/windows.

Step 3: Train your agent

For instance with Pyramids:

mlagents-learn config/ppo/PyramidsRND.yaml --env=training-envs-executables/windows/Pyramids --run-id="First Training" --no-graphics

We define four parameters:

• mlagents-learn <config>: the path where the hyperparameter config file is.
• --env: where the environment executable is.
• --run_id: the name you want to give to your training run id.
• --no-graphics: to not launch the visualization during the training (you can remove this parameter, but that might slow the training).

Step 4: Push to the Hub

mlagents-push-to-hf --run-id="First Training" --local-dir="results/First Training" --repo-id="ThomasSimonini/MLAgents-Pyramids" --commit-message="Pyramids"

We define four parameters:

• --run-id: the name of the training run id.
• --local-dir: where the agent was saved, it’s results/<run_id name>, so in my case results/First Training.
• -- repo-id: the name of the Hugging Face repo you want to create or update. It’s always <your huggingface username>/<the repo name>
• --commit-message

The Environments

ML-Agent Environment		Windows Executable	Mac Executable	Linux Executable	Visualize your agent online with Hugging Face Spaces
Pyramids		✔️	[✔️]	🏗️	✔️ https://huggingface.co/spaces/unity/ML-Agents-Pyramids
Walker		✔️	[✔️]	🏗️	✔️ https://huggingface.co/spaces/unity/ML-Agents-Walker
Worm		✔️	[✔️]	🏗️	✔️ https://huggingface.co/spaces/unity/ML-Agents-Worm
Push Block		✔️	[✔️]	🏗️	✔️ https://huggingface.co/spaces/unity/ML-Agents-Push-Block
Basic		🏗️	🏗️	🏗️	🏗️
Crawler		🏗️	🏗️	🏗️	🏗️
Wall Jump		🏗️	🏗️	🏗️	🏗️
PushBlock		🏗️	🏗️	🏗️	🏗️
3DBall: 3D Balance Ball		🏗️	🏗️	🏗️	🏗️
GridWorld		🏗️	🏗️	🏗️	🏗️
Wall Jump		🏗️	🏗️	🏗️	🏗️
Food Collector		🏗️	🏗️	🏗️	🏗️
Hallway		🏗️	🏗️	🏗️	🏗️
Soccer Twos		🏗️	🏗️	🏗️	🏗️
Strikers Vs. Goalie		🏗️	🏗️	🏗️	🏗️
Match 3		🏗️	🏗️	🏗️	🏗️
Sorter		🏗️	🏗️	🏗️	🏗️
Cooperative Push Block		🏗️	🏗️	🏗️	🏗️
Dungeon Escape		🏗️	🏗️	🏗️	🏗️