Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use gaarsmu/a2c-spider with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use gaarsmu/a2c-spider with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="gaarsmu/a2c-spider", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from gaarsmu/a2c-spider: direct link, hf CLI and curl.
- Browser
- Download file 2.14 kB
-
https://huggingface.co/gaarsmu/a2c-spider/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://gaarsmu/a2c-spider/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/gaarsmu/a2c-spider/resolve/main/vec_normalize.pkl
2.14 kB
- Xet hash:
- d277189119e294885527b1e65760de56d876cae88ed7f5372d8a060d1d1fc7d0
- Size of remote file:
- 2.14 kB
- SHA256:
- c38632cda3ebb34781396384fa4ac2c6bf84e1d51a5584eb604a387f366abe0b
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