Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use draziert/SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use draziert/SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="draziert/SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from draziert/SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 50.9 kB
-
https://huggingface.co/draziert/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://draziert/SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/draziert/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
50.9 kB
- Xet hash:
- 8a6ec8844320e90c490d474aa6da8a65fed9e0463490e47b313dea8a7d54706d
- Size of remote file:
- 50.9 kB
- SHA256:
- 9857afe258f0613ee8fff84d45d4cd5ce326ab185fe581c2cd39068c808ef8e5
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