Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Ellbendls/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Ellbendls/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Ellbendls/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from Ellbendls/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
-
https://huggingface.co/Ellbendls/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://Ellbendls/a2c-AntBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/Ellbendls/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
2.18 kB
- Xet hash:
- dfda437741a3654714b2d528b0f6dc60b92e0eb92a1fe9f0505f2712d9bca31e
- Size of remote file:
- 2.18 kB
- SHA256:
- f5d3ec5a7c8e4051d05fb81d3e6ba1c455ff3c4a5639d0161e750da294e63041
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