Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
BerzerkNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_berzerk_1111 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_berzerk_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_berzerk_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05a0fd7ed27272d426b1efe3b39edc017ea13f0cb6b5572e59e8da3dc80fd45d
- Size of remote file:
- 7.01 MB
- SHA256:
- 4f15436df5e7e58241e125ffa369c982c1c6fbc997b7ad47c33927b70181d97a
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