Reinforcement Learning
stable-baselines3
MiniGrid-Fetch-5x5-N2-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/ppo-MiniGrid-Fetch-5x5-N2-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/ppo-MiniGrid-Fetch-5x5-N2-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/ppo-MiniGrid-Fetch-5x5-N2-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from sb3/ppo-MiniGrid-Fetch-5x5-N2-v0: direct link, hf CLI and curl.
- Browser
- Download file 80.7 kB
-
https://huggingface.co/sb3/ppo-MiniGrid-Fetch-5x5-N2-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://sb3/ppo-MiniGrid-Fetch-5x5-N2-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/sb3/ppo-MiniGrid-Fetch-5x5-N2-v0/resolve/main/vec_normalize.pkl
80.7 kB
- Xet hash:
- d9c280f712e862c0546111f8e0df9f5a1a22833b91e37440eded471ad5c18260
- Size of remote file:
- 80.7 kB
- SHA256:
- 37c3c72e459a2b9c7f361ccd738fcd41d6c3623a27925ce0efb2dc6d4538f795
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