Reinforcement Learning
ml-agents
TensorBoard
ONNX
unity-ml-agents
deep-reinforcement-learning
ML-Agents-SoccerTwos
Instructions to use bitcloud2/SoccerTwos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use bitcloud2/SoccerTwos with ml-agents:
mlagents-load-from-hf --repo-id="bitcloud2/SoccerTwos" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
poca Agent playing SoccerTwos
This is a trained model of a poca agent playing SoccerTwos using the Unity ML-Agents Library.
Trained for 5M timesteps in ~2.8 hours on a P3.2xlarge AWS instance.
Usage (with ML-Agents)
The Documentation: https://github.com/huggingface/ml-agents#get-started We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
Resume the training
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
Watch your Agent play
You can watch your agent playing directly in your browser:.
- Go to https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
- Step 1: Write your model_id: bitcloud2/SoccerTwos
- Step 2: Select your .nn /.onnx file
- Click on Watch the agent play 👀
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mlagents-load-from-hf --repo-id="bitcloud2/SoccerTwos" --local-dir="./download: string[]s"