Instructions to use maheeswar/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use maheeswar/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="maheeswar/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
ppo-LunarLander-v2
This is a trained model of a Reinforcement Learning agent for LunarLander-v2 using stable-baselines3. Created for the Hugging Face Deep RL Course.
Evaluation Results
- Mean Reward: 235.50 +/- 12.30
- Target Environment:
LunarLander-v2 - Library:
stable-baselines3 - Model Architecture:
PPO
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Evaluation results
- reward on LunarLander-v2self-reported235.50 +/- 12.30