Thread

1. nico · 1790006937 · focus · HN ↗

   If you only need classification, and you can provide some training data, you can ask Codex/Claude to build an embeddings + logistic classifier model for you

   For emails, I get 95% accuracy with this method, with only 50-100 examples for training

   Training the model takes less than 5 minutes on a CPU

   The resulting model is <1MB, and inference is sub 100ms

   Some other cool things about this approach:

   * the model doesn’t train on some “ideal” or general classification, instead it learns your preferences

   * the model runs on pretty much any mobile device and can be retrained online on the device

   * privacy, the whole training and inference is 100% local, no data goes anywhere (except whatever you feed codex/claude while building the model)

   Note: to do a more general test, I made a classifier for the Banking77 dataset. The model is <10MB, trains in <30s on CPU and gets 94.5% accuracy, which puts it in the top 5?models by accuracy for that set (the best one is at 94.86%, but it’s 350MB in size and takes hours to train on a GPU).

   1. tk90 · 1790034038 · focus · HN ↗

      I'm working on exactly this! I'm building a small model that classifies the correct DOM node containing an HTML's article content/title/date/author (given a raw html with a lot of noise/chrome). A fun learning exercise :)

      30KB model, 40-50ms inference. Pretty happy with the results so far!

      I can see an entire industry of tiny models like this, now that we have AI to help us do the grunt setup work (validation/training data creation, data cleaning, etc). Or just use a general classifier like Jev/Kev ha

      1. bicepjai · 1790044572 · focus · HN ↗

         Is this like for cleaning html data from say common crawl ?

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