Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use swaroop06/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use swaroop06/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="swaroop06/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
PPO agent playing LunarLander-v2
This is a trained model of an PPO agent playing LunarLander-v2 for the Hugging Face Deep Reinforcement Learning Course (Unit 1).
Evaluation Results
- Mean Reward: 285.50 +/- 15.20
- Environment: LunarLander-v2
- Algorithm: PPO
- Library: stable-baselines3
Usage
Trained and evaluated for the Hugging Face Deep RL Course certification.
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Evaluation results
- mean_reward on LunarLander-v2self-reported285.50 +/- 15.20