Instructions to use rohit0128/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use rohit0128/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="rohit0128/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
ppo-LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2. This model was trained as part of the Hugging Face Deep Reinforcement Learning Course.
Evaluation Results
- Environment:
LunarLander-v2 - Algorithm:
PPO - Library:
stable-baselines3 - Mean Reward:
285.50 +/- 8.50
Usage
To evaluate this model locally or play with it, download the model files from this repository.
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Evaluation results
- mean_reward on LunarLander-v2self-reported285.50 +/- 8.50