Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PongNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_pong_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_pong_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_pong_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 374e7627e81db22e670d95a57b9e972f18bb8a4b84dd2968937dcb32cae67a4b
- Size of remote file:
- 6.98 MB
- SHA256:
- 020dbce0330a9194e516d4c81ab56fa5b2a25cf69ab2b6a5092f95681d6c8b53
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