Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use rishipatel92/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use rishipatel92/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="rishipatel92/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from rishipatel92/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.52 kB
-
https://huggingface.co/rishipatel92/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://rishipatel92/a2c-AntBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/rishipatel92/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
2.52 kB
- Xet hash:
- e21644aa1e4dada55752929570a5629a4849dc497d7c4a475a8fe6eef6ed9148
- Size of remote file:
- 2.52 kB
- SHA256:
- 3ece66537162f180c073da47b7d7e72008459ee8ba2e53c213f5970ae9290b04
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