Category

Research

Posts

All
Research
All
Resources
All
Updates
Research

NuExtract 1.5 - Multilingual, Infinite context, still small, and better than GPT-4o!

We introduce NuExtract 1.5, the new version of our foundation model for structured extraction. NuExtract 1.5 is multilingual, can handle arbitrarily long documents, and outperforms GPT-4o in English while being 500 times smaller. As usual, we release it under MIT license.

July 16, 2024
NuExtract 1.5 - Multilingual, Infinite context, still small, and better than GPT-4o!
Research

NuExtract: A Foundation Model for Structured Extraction

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 model can be directly used in a zero-shot setting or fine-tuned to solve a specific extraction problem. As usual, we open-source it under MIT license for everyone to use.

July 16, 2024
NuExtract: A Foundation Model for Structured Extraction
Research

A Foundation Model for Entity Recognition

Entity recognition is a widely used information extraction task, yet publicly available foundation models are not well suited for it. We leverage modern LLMs to create a small-yet-powerful foundation model for this task. This BERT-size model can be used to create custom entity recognizers with typically 5x less annotated data than before. This model is powering NuMind and we open-source it with an MIT license for everyone to use. Spread the word!

July 16, 2024
A Foundation Model for Entity Recognition
Research

Creating Task-Specific Foundation Models with GPT-4

There are two kinds of BERT-size NLP models in this world: general-purpose ones (a.k.a. foundation models), and highly specialized ones, trained on specific tasks and data. Neither kind is ideal to solve particular NLP problems on your data. We need to fill this specialization gap with task-specific foundation models, and propose a way to create them efficiently using LLMs. We apply this method to create a state-of-the-art domain-agnostic foundation model for Sentiment Analysis that we open source for everyone to use.

July 16, 2024
Creating Task-Specific Foundation Models with GPT-4