Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Behnam/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Behnam/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Behnam/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from Behnam/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.17 kB
-
https://huggingface.co/Behnam/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://Behnam/a2c-AntBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/Behnam/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
2.17 kB
- Xet hash:
- fb467c1a184a6efe2b4a87e23e6e67119e5aa9ebcce59fb3b503388e2c9fa402
- Size of remote file:
- 2.17 kB
- SHA256:
- 50eac6d6b79856b71bbb856702b20c6cdd996bc83c847f28007c11cd803420b8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.