Saturday, 16th November 2024
NuExtract 1.5. Structured extraction - where an LLM helps turn unstructured text (or image content) into structured data - remains one of the most directly useful applications of LLMs.
NuExtract is a family of small models directly trained for this purpose (though text only at the moment) and released under the MIT license.
It comes in a variety of shapes and sizes:
- NuExtract-v1.5 is a 3.8B parameter model fine-tuned on Phi-3.5-mini instruct. You can try this one out in this playground.
- NuExtract-tiny-v1.5 is 494M parameters, fine-tuned on Qwen2.5-0.5B.
- NuExtract-1.5-smol is 1.7B parameters, fine-tuned on SmolLM2-1.7B.
All three models were fine-tuned on NuMind's "private high-quality dataset". It's interesting to see a model family that uses one fine-tuning set against three completely different base models.
Useful tip from Steffen Röcker:
Make sure to use it with low temperature, I've uploaded NuExtract-tiny-v1.5 to Ollama and set it to 0. With the Ollama default of 0.7 it started repeating the input text. It works really well despite being so smol.
Project: Civic Band—scraping and searching PDF meeting minutes from hundreds of municipalities
I interviewed Philip James about Civic Band, his “slowly growing collection of databases of the minutes from civic governments”. Philip demonstrated the site and talked through his pipeline for scraping and indexing meeting minutes from many different local government authorities around the USA.
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