Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use messham/LunarLander_Course2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use messham/LunarLander_Course2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="messham/LunarLander_Course2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download results.json from messham/LunarLander_Course2: direct link, hf CLI and curl.
- Browser
- Download file 164 Bytes
-
https://huggingface.co/messham/LunarLander_Course2/resolve/main/results.json
- Command line
-
hf download hf://messham/LunarLander_Course2/results.json
-
curl -L -o results.json https://huggingface.co/messham/LunarLander_Course2/resolve/main/results.json
164 Bytes
| {"mean_reward": 259.86240197051154, "std_reward": 20.76367924748218, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-17T15:18:23.246334"} |