Reinforcement Learning
stable-baselines3
MiniGrid-FourRooms-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/ppo-MiniGrid-FourRooms-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/ppo-MiniGrid-FourRooms-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/ppo-MiniGrid-FourRooms-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from sb3/ppo-MiniGrid-FourRooms-v0: direct link, hf CLI and curl.
- Browser
- Download file 80.7 kB
-
https://huggingface.co/sb3/ppo-MiniGrid-FourRooms-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://sb3/ppo-MiniGrid-FourRooms-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/sb3/ppo-MiniGrid-FourRooms-v0/resolve/main/vec_normalize.pkl
80.7 kB
- Xet hash:
- c43e43a8421afc84fb2a2d92c560ccf1c6873e3996cef66e80aeefc2ea4bf027
- Size of remote file:
- 80.7 kB
- SHA256:
- fa5090c644ff7dce397a98a2b0db302858d88bf7cb464ccfe914e4147e01cf62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.