Reinforcement Learning
stable-baselines3
LunarLander-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use hellosara/ppo-LunarLander-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use hellosara/ppo-LunarLander-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="hellosara/ppo-LunarLander-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
| library_name: stable-baselines3 | |
| tags: | |
| - LunarLander-v3 | |
| - deep-reinforcement-learning | |
| - reinforcement-learning | |
| - stable-baselines3 | |
| model-index: | |
| - name: PPO | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: LunarLander-v3 | |
| type: LunarLander-v3 | |
| metrics: | |
| - type: mean_reward | |
| value: 262.16 +/- 22.42 | |
| name: mean_reward | |
| verified: false | |
| # This line tells Hugging Face to show your video on the front page | |
| video: https://huggingface.co/hellosara/ppo-LunarLander-v3/resolve/main/replay.mp4 | |