Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use realsanjeev/SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use realsanjeev/SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="realsanjeev/SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from realsanjeev/SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 36.8 kB
-
https://huggingface.co/realsanjeev/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://realsanjeev/SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/realsanjeev/SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
36.8 kB
- Xet hash:
- 7fbf8d8ef02119e0c03aa97d6a564e6ec1ef0991ce9bd44f64d4dc2c99f606d6
- Size of remote file:
- 36.8 kB
- SHA256:
- 0f46de5de9cb972f5a26e82a1785967dfe64381e4ae9a61f1e52bb2fcc83dd82
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