Reinforcement Learning
stable-baselines3
BipedalWalker-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/ppo-BipedalWalker-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/ppo-BipedalWalker-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/ppo-BipedalWalker-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from sb3/ppo-BipedalWalker-v3: direct link, hf CLI and curl.
- Browser
- Download file 131 kB
-
https://huggingface.co/sb3/ppo-BipedalWalker-v3/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://sb3/ppo-BipedalWalker-v3/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/sb3/ppo-BipedalWalker-v3/resolve/main/train_eval_metrics.zip
131 kB
- Xet hash:
- 5c093a8253ee56bd074daa8c9816843321a8d0708575dbad1774d6d26e5f8848
- Size of remote file:
- 131 kB
- SHA256:
- ca925e4485bbd636449ace1c1a12c37a34c49c5a2a6675643b0ecdbb8dc75f27
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