Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use salamentic/Chapter1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use salamentic/Chapter1 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="salamentic/Chapter1", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download Pog/policy.pth from salamentic/Chapter1: direct link, hf CLI and curl.
- Browser
- Download file 43.4 kB
-
https://huggingface.co/salamentic/Chapter1/resolve/main/Pog/policy.pth
- Command line
-
hf download hf://salamentic/Chapter1/Pog/policy.pth
-
curl -L -o policy.pth https://huggingface.co/salamentic/Chapter1/resolve/main/Pog/policy.pth
43.4 kB
- Xet hash:
- 873c4d86cd41e22d1a7ba63f5f02e6f68dcf6adfdd1b1e3b0b90c311d6ccb96a
- Size of remote file:
- 43.4 kB
- SHA256:
- 04033dd26d011ac5f6ed840c4d25bfadea94895b18013237d4a389bba08b8f7e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.