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[ARTICLE · art-40210] src=news.ycombinator.com ↗ pub= topic=machine-learning verified=true sentiment=· neutral

Overfitted a 900KB Transformer to Compress a 100MB CSV into 7MB

A developer built an experiment using an overfitted 900KB transformer and arithmetic coding to compress individual files, achieving 7MB compression on a 100MB NYC taxi CSV and 21MB on a 100MB enwik9 slice, though compression and decompression are slow at around 45 minutes each.

read1 min views12 publishedJun 23, 2026

| |||||||||||||||||||||||||||||||||||||||||||| 22 points by | I built an experiment that uses an overfitted transformer and arithmetic coding to compress individual files. Instead of training the model to generalize, I train a 900KB transformer to memorize a single file and predict the next byte. Those predictions are fed into an arithmetic coder to produce the compressed output. On a 100MB NYC taxi CSV, it compresses to about 7MB (~0.5 bits/byte). On a 100MB slice of enwik9, it compresses to about 21MB (~1.68 bits/byte). It's pretty slow right now (roughly 20–30 minutes of training and 45 minutes each for compression and decompression on my AMD 7800XT). Checkout the repo - https://github.com/samyak112/pym-particles | ||||||||||||||||||||||||||||||||||||||||||| |

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