Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use baronase/unit3-atari-dqn-1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use baronase/unit3-atari-dqn-1m with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="baronase/unit3-atari-dqn-1m", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download replay.mp4 from baronase/unit3-atari-dqn-1m: direct link, hf CLI and curl.
- Browser
- Download file 218 kB
-
https://huggingface.co/baronase/unit3-atari-dqn-1m/resolve/main/replay.mp4
- Command line
-
hf download hf://baronase/unit3-atari-dqn-1m/replay.mp4
-
curl -L -o replay.mp4 https://huggingface.co/baronase/unit3-atari-dqn-1m/resolve/main/replay.mp4
218 kB
- Xet hash:
- 7ee0f8618790b0f4b7ad3e5517533ec49a221d73d7100564791fe46546a39591
- Size of remote file:
- 218 kB
- SHA256:
- 0fc03bd19808f3c476b1d918281071894608b203b74146b93b8aaf83476df834
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