Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Rishi26x/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Rishi26x/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Rishi26x/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
ppo-LunarLander-v2 Agent playing LunarLander-v2
This is a trained model of a ppo-LunarLander-v2 agent playing LunarLander-v2 using the stable-baselines3 library. Trained for the Hugging Face Deep Reinforcement Learning Course.
Evaluation Results
- Mean Reward: 275.81
- Std Reward: 26.46
- Score (Mean - Std): 249.35
- Downloads last month
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Evaluation results
- mean_reward on LunarLander-v2self-reported275.81 +/- 26.46