Reinforcement Learning
stable-baselines3
AntBulletEnv-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use pratsy/a2c-AntBulletEnv-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use pratsy/a2c-AntBulletEnv-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="pratsy/a2c-AntBulletEnv-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54c87da8179aedcce058089f22c50aea0db77d6c48d34b4ac8b05d571a6f5e29
- Size of remote file:
- 2.18 kB
- SHA256:
- bae4141e9bffb27aaab27644c6b3f11f9324737ab265f62b2dbd97c7796e56bb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.