Reinforcement Learning
stable-baselines3
Walker2DBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Chris1/a2c-Walker2DBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Chris1/a2c-Walker2DBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Chris1/a2c-Walker2DBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from Chris1/a2c-Walker2DBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.49 kB
-
https://huggingface.co/Chris1/a2c-Walker2DBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://Chris1/a2c-Walker2DBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/Chris1/a2c-Walker2DBulletEnv-v0/resolve/main/vec_normalize.pkl
2.49 kB
- Xet hash:
- 28b5dc9d75465a2beae604df994bbc262c8547b58489fb8a317c824381be446b
- Size of remote file:
- 2.49 kB
- SHA256:
- 00d542cd2fee23be9553a0a96ee505a7a2bbd729d7fd53648100bd2d2b584caf
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