Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use hackvermin/dqn-atari with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use hackvermin/dqn-atari with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="hackvermin/dqn-atari", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download train_eval_metrics.zip from hackvermin/dqn-atari: direct link, hf CLI and curl.
- Browser
- Download file 37 kB
-
https://huggingface.co/hackvermin/dqn-atari/resolve/main/train_eval_metrics.zip
- Command line
-
hf download hf://hackvermin/dqn-atari/train_eval_metrics.zip
-
curl -L -o train_eval_metrics.zip https://huggingface.co/hackvermin/dqn-atari/resolve/main/train_eval_metrics.zip
37 kB
- Xet hash:
- 877627b5a7efb3cd2c848c3b4b4b540d40618051dacb88b541a65add3d4658e7
- Size of remote file:
- 37 kB
- SHA256:
- d9659d13c97ab61aa1e80c3d83ec3f73a6370b13ac315db084c91921312d3d78
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