kopia lustrzana https://github.com/thinkst/zippy
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@ -6,7 +6,7 @@ its training data to calculate the probability of each word given the preceeding
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the more high-probability tokens are more likely to be AI-originated. Techniques and tools in this repo are looking for
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faster approximation to be embeddable and more scalable.
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## LZMA compression detector (`lzma_detect.py` and `nlzmadetect`)
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## LZMA compression detector (`zippy.py` and `nlzmadetect`)
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ZipPy uses the LZMA compression ratios as a way to indirectly measure the perplexity of a text.
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Compression ratios have been used in the past to [detect anomalies in network data](http://owncloud.unsri.ac.id/journal/security/ontheuse_compression_Network_anomaly_detec.pdf)
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