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README.md

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-license: cc0-1.0
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+---
+license: cc0-1.0
+---
+
+# 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 using repos like [Jasmine](https://github.com/p-doom/jasmine).
+
+---
+
+### Dataset Summary
+- **Environment:** CoinRun (Procgen Benchmark)  
+- **Frames:** 50 million  
+- **Resolution:** 64 × 64  
+- **Format:** [`ArrayRecord`](https://github.com/google/array_record) (for fast I/O)  
+- **Splits:** `train` / `val` / `test`  
+- **License:** [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)  
+
+---
+
+## Usage
+This dataset it part of the [Jasmine](https://github.com/p-doom/jasmine) repository release. Frames were collected from random agent rollouts. 
+
+The ArrayRecord format enables efficient dataloading using Grain ([Jasmine](https://github.com/p-doom/jasmine/blob/main/jasmine/utils/dataloader.py)).
+
+## Citation
+
+If you use our CoinRun dataset, please cite our work:
+
+```tex
+@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}
+}