Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
GopherNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_gopher_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_gopher_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_gopher_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
Download agent.pt from edbeeching/atari_2B_atari_gopher_1111: direct link, hf CLI and curl.
- Browser
- Download file 6.99 MB
-
https://huggingface.co/edbeeching/atari_2B_atari_gopher_1111/resolve/main/agent.pt
- Command line
-
hf download hf://edbeeching/atari_2B_atari_gopher_1111/agent.pt
-
curl -L -o agent.pt https://huggingface.co/edbeeching/atari_2B_atari_gopher_1111/resolve/main/agent.pt
6.99 MB
- Xet hash:
- 888c8a951260fa0e86326de9173399c7ce48f6d34b175e35d8efa6b02ce08446
- Size of remote file:
- 6.99 MB
- SHA256:
- 24fa878c73bc4500ad8d5cbb39f0eddaca05273a443efb548353726aa2f56bc9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.