Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use WDong/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use WDong/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="WDong/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from WDong/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 36.5 kB
-
https://huggingface.co/WDong/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://WDong/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/WDong/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
36.5 kB
- Xet hash:
- e8d9327755695fa800dd03f987dc95284974ac9687fa16dfec61f0c3fce6da46
- Size of remote file:
- 36.5 kB
- SHA256:
- a308afb2a5e1c84809076cfa37151a91b3ea0d144e8b9f2b04d5b6e4d4b1c91a
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