Reinforcement Learning
ml-agents
TensorBoard
ONNX
unity-ml-agents
Huggy
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use swaroop06/ppo-Huggy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ml-agents
How to use swaroop06/ppo-Huggy with ml-agents:
mlagents-load-from-hf --repo-id="swaroop06/ppo-Huggy" --local-dir="./download: string[]s"
- Notebooks
- Google Colab
- Kaggle
PPO agent playing Huggy
This is a trained model of an PPO agent playing Huggy for the Hugging Face Deep Reinforcement Learning Course (Bonus Unit 1).
Evaluation Results
- Mean Reward: 15.00 +/- 1.50
- Environment: Huggy
- Algorithm: PPO
- Library: ml-agents
Usage
Trained and evaluated for the Hugging Face Deep RL Course.
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Evaluation results
- mean_reward on Huggyself-reported15.00 +/- 1.50