Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jinukoo/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jinukoo/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jinukoo/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from jinukoo/a2c-AntBulletEnv-v0: direct link, hf CLI and curl.
- Browser
- Download file 2.14 kB
-
https://huggingface.co/jinukoo/a2c-AntBulletEnv-v0/resolve/d65b18a0946ff5d8860c32b08c5536a7521ae816/vec_normalize.pkl
- Command line
-
hf download hf://jinukoo/a2c-AntBulletEnv-v0@d65b18a0946ff5d8860c32b08c5536a7521ae816/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/jinukoo/a2c-AntBulletEnv-v0/resolve/d65b18a0946ff5d8860c32b08c5536a7521ae816/vec_normalize.pkl
2.14 kB
- Xet hash:
- 2013e0cd3fb941cafaea50811500d524e17295fecd840d503d68ce9dd07825ff
- Size of remote file:
- 2.14 kB
- SHA256:
- 3a545846507d0e03dfc95bdfa8fb573781ad256acf37f471736abfc845ad0373
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.