Reinforcement Learning
stable-baselines3
Walker2DBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/a2c-Walker2DBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/a2c-Walker2DBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/a2c-Walker2DBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from sb3/a2c-Walker2DBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/sb3/a2c-Walker2DBulletEnv-v0/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://sb3/a2c-Walker2DBulletEnv-v0/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/sb3/a2c-Walker2DBulletEnv-v0/resolve/main/vec_normalize.pkl
5.27 kB
- Xet hash:
- 559bb00bd292bea03eceeb6f2514ef24e93bc41b525f5d91ccc7691fc20fa942
- Size of remote file:
- 5.27 kB
- SHA256:
- 399de2cd6ea1ded1e871dde4c8369f1c3cf33b99812a05aa25ca3c6d8f68bbc5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.