Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
AsteroidsNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_asteroid_2222 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_asteroid_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_asteroid_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
Download replay.mp4 from edbeeching/atari_2B_atari_asteroid_2222: direct link, hf CLI and curl.
- Browser
- Download file 2.22 MB
-
https://huggingface.co/edbeeching/atari_2B_atari_asteroid_2222/resolve/main/replay.mp4
- Command line
-
hf download hf://edbeeching/atari_2B_atari_asteroid_2222/replay.mp4
-
curl -L -o replay.mp4 https://huggingface.co/edbeeching/atari_2B_atari_asteroid_2222/resolve/main/replay.mp4
2.22 MB
- Xet hash:
- a641dc06a34b53d65b3ebdaae1e17e3b236f4748e3f235069828ad72970619ee
- Size of remote file:
- 2.22 MB
- SHA256:
- 5eec72d958a291dd99a2baf5bc5e88172ac9dad27a88b5ea1603c5aa52bb91ef
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