Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
GopherNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_gopher_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_gopher_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_gopher_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebe3ce5bdf8657bbb479fc99ddcffd6b46a1aeb5b9bfe1c69e2818748467b12f
- Size of remote file:
- 6.99 MB
- SHA256:
- 0b401992c2e1c023299a478f8f0137c92d87fdb357854717e7a5c0f199e8d343
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