self-play-pretrain-zero-data

Self-Play Pretraining with Zero Data (wip)

Implementation of Self-Play Pretraining with Zero Data

Citations

@misc{cowsik2026selfplaypretrainingzerodata,
    title    = {Self-Play Pretraining with Zero Data},
    author   = {Aditya Cowsik and Kfir Dolev and Michael Y. Li and G. Bruno De Luca and Nourya Cohen and Noah D. Goodman and Yoav Levine},
    year     = {2026},
    eprint   = {2609.30063},
    archivePrefix = {arXiv},
    primaryClass = {cs.AI},
    url      = {https://arxiv.org/abs/2609.30063},
}

@software{Morehead_JVP_Flash_Attention_2025,
    author  = {Morehead, Alex},
    doi     = {10.5281/zenodo.17050188},
    license = {MIT},
    month   = {sep},
    title   = {JVP Flash Attention},
    url     = {https://github.com/amorehead/jvp_flash_attention},
    version = {0.14.0},
    year    = {2025}
}

@misc{bloem2025universalpretrainingiteratedrandom,
    title   = {Universal pre-training by iterated random computation},
    author  = {Peter Bloem},
    year    = {2025},
    eprint  = {2506.20057},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/2506.20057},
}

Metadata

Release files for self-play-pretrain-zero-data 0.0.9

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Source distribution for self-play-pretrain-zero-data 0.0.9
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Built distribution (wheel)

Table of built distributions (wheels) for self-play-pretrain-zero-data 0.0.9
File	Interpreter	ABI	Platform	Reset
self_play_pretrain_zero_data-0.0.9-py3-none-any.whl 14.6 kB Oct 3, 2026	Python 3	none	any	Details

Total release size: 27.6 kB

Release files / self_play_pretrain_zero_data-0.0.9.tar.gz

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Download URL	self_play_pretrain_zero_data-0.0.9-py3-none-any.whl
Size	14.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`3b5f60bc423cc8569b876bce44e285e608187dee1f1a31750c21987094b90154`
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Uploaded via	`uv/0.8.17`