Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use Lily96/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Lily96/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Lily96/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from Lily96/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 36.7 kB
-
https://huggingface.co/Lily96/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://Lily96/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/Lily96/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
36.7 kB
- Xet hash:
- 4bd9caa283ee34bc4f9adb03b0db264723b5b96616aca7e2f1f82eee040dc7fc
- Size of remote file:
- 36.7 kB
- SHA256:
- 441c1ef12fdba5a824e9ec77212d836d04ab060c1b4eb7561bbe506fb67b0b07
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