Reinforcement Learning
stable-baselines3
LunarLander-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use yDiffraction/Reinforcement-Learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use yDiffraction/Reinforcement-Learning with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="yDiffraction/Reinforcement-Learning", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download first/policy.optimizer.pth from yDiffraction/Reinforcement-Learning: direct link, hf CLI and curl.
- Browser
- Download file 88.7 kB
-
https://huggingface.co/yDiffraction/Reinforcement-Learning/resolve/main/first/policy.optimizer.pth
- Command line
-
hf download hf://yDiffraction/Reinforcement-Learning/first/policy.optimizer.pth
-
curl -L -o policy.optimizer.pth https://huggingface.co/yDiffraction/Reinforcement-Learning/resolve/main/first/policy.optimizer.pth
88.7 kB
- Xet hash:
- 9a866dffb8058d73c337a09dc579811238a0bc87a0ec1716f4b59ea5b933d636
- Size of remote file:
- 88.7 kB
- SHA256:
- 2856e3b6dc3ad687256a7931c67222a569cb49298bb9128b2c268dd44e8936c1
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