Introducing LiqFit framework - New revolutionized way of NLP model fine-tuning


Posted January 26, 2024 by knowledgator

LiqFit is a new framework for few-shot learning of NLP models. It's easy to use and incredibly effective for tasks like text classification, NER, and other information extraction tasks, achieving competitive results with just 8 examples per label!

 
We're thrilled to announce the launch of LiqFit - the new go-to library for flexible few-shot learning of cross-encoder models.

🔍 What's LiqFit?
LiqFit is not just another library, it's a revolution in few-shot learning. Perfect for tasks ranging from text classification to question-answering, LiqFit stands out with its ability to work wonders with minimal data. Imagine achieving top-notch results with just 8 examples per label - that's the power of LiqFit!

Available on the Github: https://github.com/Knowledgator/LiqFit

🌟 Framework features:

- Only a few examples are needed 🎯
- Versatile for various info-extraction tasks 📝
- Adapts to classes not presented in the training set 🌈
- Supports various cross-encoder types ⚙️
- Handles unbalanced datasets well ⚖️
- Perfect for multi-label classification 🏷️

Follow us on social media for new upcoming releases: https://www.knowledgator.com/
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Issued By Knowledgator Engineering
Business Address 2ND FLOOR COLLEGE HOUSE, 17 KING EDWARDS ROAD
Country United Kingdom
Categories Software , Technology
Tags machine learning , artificial intelligence , natural language processing , information extraction , named entity recognition
Last Updated January 26, 2024