Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use J4F4N4F/SpaceInvader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use J4F4N4F/SpaceInvader with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="J4F4N4F/SpaceInvader", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from J4F4N4F/SpaceInvader: direct link, hf CLI and curl.
- Browser
- Download file 21.8 kB
-
https://huggingface.co/J4F4N4F/SpaceInvader/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://J4F4N4F/SpaceInvader/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/J4F4N4F/SpaceInvader/resolve/main/train_eval_metrics.zip
21.8 kB
- Xet hash:
- 2ca8d275fa14ee609ef53ca53053da132ea4e41e4880d4df3497ec56f66edb0f
- Size of remote file:
- 21.8 kB
- SHA256:
- 384c4874de5467c0d8302c0d1b4c52b18a031da7151faa7d2526e9ee958ad0b0
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