Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use optimopium/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use optimopium/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="optimopium/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from optimopium/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.18 kB
-
https://huggingface.co/optimopium/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://optimopium/a2c-AntBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/optimopium/a2c-AntBulletEnv-v0/resolve/main/vec_normalize.pkl
2.18 kB
- Xet hash:
- 786da3c0e17d3f137aa790c7b419cae6bc93cddf9776192b9eb1a57698b1c556
- Size of remote file:
- 2.18 kB
- SHA256:
- 502ac7984a080d37f7c383eb22753407307c07313d59e198847e8cf8f17edf33
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