Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sb3/ppo-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sb3/ppo-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sb3/ppo-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from sb3/ppo-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 456 kB
-
https://huggingface.co/sb3/ppo-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://sb3/ppo-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/sb3/ppo-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
456 kB
- Xet hash:
- c3cda6ff881cbc370c8b6ed1c2482fcf73bd94fb7f25c60a3fee5aa79b1d1e5c
- Size of remote file:
- 456 kB
- SHA256:
- d6e53d5cba81b873d6fee3016eec0e64c1ef9a1229bbe8ac9c4cdcb7d07a96ad
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