Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sangioai/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sangioai/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sangioai/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from sangioai/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 8.61 kB
-
https://huggingface.co/sangioai/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://sangioai/dqn-SpaceInvadersNoFrameskip-v4/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/sangioai/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/train_eval_metrics.zip
8.61 kB
- Xet hash:
- fe4d06a5a950658105a67d25d9c23bbba572567c3d0653ca53e4195231459674
- Size of remote file:
- 8.61 kB
- SHA256:
- 7e4bd03ce896519c5246e466553f7ca5beeda49e065fc862cf3c9a31673800a1
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