p-doom/coinrun-dataset

CoinRun Dataset

This is a large dataset of 50M video frames and actions collected from the CoinRun environment (Cobbe et al., 2020) for training world models.
The dataset enables reproducible, large-scale experiments in action-conditioned video prediction. It is meant to be used with Jasmine, our JAX-based world modeling codebase.

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Dataset Summary

• Environment: CoinRun (Procgen Benchmark)
• Frames: 50 million
• Resolution: 64 × 64
• Format: ArrayRecord (for fast I/O)
• Splits: train / val / test
• License: CC0 1.0

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Usage

This dataset is part of the Jasmine repository release. Frames were collected from random agent rollouts.

The ArrayRecord format enables efficient dataloading using Grain and is optimized for the Jasmine dataloader.

You can download the dataset using the huggingface-cli tool.

huggingface-cli download --repo-type dataset p-doom/coinrun-dataset --local-dir <data_path>

To start a training run using Jasmine, simply pass the train and val split to the training script.

python jasmine/baselines/maskgit/train_tokenizer_vqvae.py \
    --data_dir <data_path>/train \
    --val_data_dir <data_path>/val \
    ...

Citation

If you use our CoinRun dataset, please cite our work:

@article{
    mahajan2025jasmine,
    title={Jasmine: A simple, performant and scalable JAX-based world modeling codebase},
    author={Mihir Mahajan and Alfred Nguyen and Franz Srambical and Stefan Bauer},
    journal = {p(doom) blog},
    year={2025},
    url={https://pdoom.org/jasmine.html},
    note = {https://pdoom.org/blog.html}
}