Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Ditrip/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Ditrip/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Ditrip/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from Ditrip/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
-
https://huggingface.co/Ditrip/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://Ditrip/a2c-AntBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/Ditrip/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
2.18 kB
- Xet hash:
- bb1f5ab027fc2d95e9b910222d5b1d876c5032237a4d33e3479c6e7041a7c7ec
- Size of remote file:
- 2.18 kB
- SHA256:
- f3fccbde8fff5e4ab9a4419e813c8fc74a7a7a7c43c69fad36162bc4e2e8a1f1
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