Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jefsnacker/rl_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jefsnacker/rl_class with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jefsnacker/rl_class", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| library_name: stable-baselines3 | |
| tags: | |
| - LunarLander-v2 | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - stable-baselines3 | |
| model-index: | |
| - name: PPO | |
| results: | |
| - metrics: | |
| - type: mean_reward | |
| value: 284.52 +/- 16.29 | |
| name: mean_reward | |
| task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: LunarLander-v2 | |
| type: LunarLander-v2 | |
| # **PPO** Agent playing **LunarLander-v2** | |
| This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). | |
| ## Usage (with Stable-baselines3) | |
| TODO: Add your code | |