Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use plpanjali05/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use plpanjali05/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="plpanjali05/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
PPO Agent playing LunarLander-v2
This is a trained model of an agent playing LunarLander-v2 using the stable-baselines3 library as part of the Hugging Face Deep Reinforcement Learning Course.
- Environment: LunarLander-v2
- Library: stable-baselines3
- Mean Reward: 265.50 +/- 18.20
- Student: plpanjali05
Usage
# To load this model, refer to the corresponding unit notebook in the Hugging Face Deep RL Course.
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Evaluation results
- mean_reward on LunarLander-v2self-reported265.50 +/- 18.20