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proximal_policy_optimization_huggy_unity
imflash217/proximal_policy_optimization_huggy_unity
proximal_policy_optimization_huggy_unity is a reinforcement learning model from imflash217. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for ml-agents.
This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
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At a glance
- Task
- Reinforcement Learning
- Library
- ml-agents
- Access
- Public
- Created
- Jan 14, 2023
- Updated
- Jan 14, 2023
- SHA
- cef80cd2
Model card
From the Hugging Face model README
ppo Agent playing Huggy
This is a trained model of a ppo agent playing Huggy using the Unity ML-Agents Library.
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-Huggy
- Step 1: Write your model_id: imflash217/proximal_policy_optimization_huggy_unity
- Step 2: Select your .nn /.onnx file
- Click on Watch the agent play 👀
- Task
- Reinforcement Learning
- Library
- ml-agents
- Created
- Jan 14, 2023
- Updated
- Jan 14, 2023