Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
KangarooNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_kangaroo_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_kangaroo_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_kangaroo_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
Download replay.mp4 from edbeeching/atari_2B_atari_kangaroo_2222: direct link, hf CLI and curl.
- Browser
- Download file 87.1 kB
-
https://huggingface.co/edbeeching/atari_2B_atari_kangaroo_2222/resolve/main/replay.mp4
- Command line
-
hf download hf://edbeeching/atari_2B_atari_kangaroo_2222/replay.mp4
-
curl -L -o replay.mp4 https://huggingface.co/edbeeching/atari_2B_atari_kangaroo_2222/resolve/main/replay.mp4
87.1 kB