We introduce NuExtract, a lightweight text-to-JSON LLM. NuExtract allows to extract arbitrarily complex information from text and turns it into structured data.
This article explores NuExtract, a family of Small Language Models (SLMs) for extracting structured data from text. The author, Fabio Matricardi, discusses using NuExtract to process candidate CVs for a database and highlights its benefits for privacy protection and running on less powerful computers.
NuExtract is a fine-tuned version of phi-3-mini for information extraction. It requires a JSON template describing the information to extract and an input text. Provides tiny (0.5B) and large (7B) versions.
NuExtract is a 3.8B parameter information extraction model fine-tuned from phi-3, designed to extract structured data from text using a JSON template.
A prompt template containing prompting techniques that have worked for the author on over a dozen nuanced medical information extraction tasks.
Extract structured data from remote or local LLM models. Predictable output is essential for any serious use of LLMs.
Extract data into Pydantic objects, dataclasses or simple types.
Same API for local file models and remote OpenAI, Mistral AI and other models.
Model management: download models, manage configuration, quickly switch between models.
Tools for evaluating output across local/remote models, for chat-like interaction and more.
No matter how well you craft a prompt begging a model for the output you need, it can always respond something else. Extracting structured data can be a big step into getting predictable behavior from your models.
Extract data into Pydantic objects, dataclasses or simple types.
Same API for local file models and remote OpenAI, Mistral AI and other models.
Model management: download models, manage configuration, quickly switch between models.
Tools for evaluating output across local/remote models, for chat-like interaction and more.
No matter how well you craft a prompt begging a model for the output you need, it can always respond something else. Extracting structured data can be a big step into getting predictable behavior from your models.
