This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
Model source
Source excerpt
This is a trained model of a ppo agent playing Pyramids using the Unity ML-Agents Library.
Sources
1 sourceVerified Aug 19
Model artifacts
8 artifactsSource excerpts
3 excerptsPyramids/Pyramids-1000364.onnx
onnx · 1.35 MB · SHA-256 60bf55df6148…057e · Hugging Face
--- library_name: ml-agents tags: - Pyramids - deep-reinforcement-learning - reinforcement-learning - ML-Agents-Pyramids --- # **ppo** Agent playing **Pyramids** This is a trained model of a **ppo** agent playing **Pyramids** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). ## Usage (with ML-Agents) The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ 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: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction - A *longer tutorial* to understand how works ML-Agents: https://huggingface.co/learn/deep-rl-course/unit5/introduction ### Resume the training ```bash 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** 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity 2. Step 1: Find your model_id: sanju-1007/ML-Agents-Pyramids 3. Step 2: Select your *.nn /*.onnx file 4. Click on Watch the agent play 👀
Source context: 11 downloads · 0 likes · Pipeline reinforcement-learning · Library ml-agents · Repo sanju-1007/ML-Agents-Pyramids
Source context: 8 downloads · 0 likes · Pipeline reinforcement-learning · Library ml-agents · Repo sanju-1007/ML-Agents-Pyramids