declare-lab/KNOT
This repository contains the implementation of the paper -- KNOT: Knowledge Distillation using Optimal Transport for Solving NLP Tasks
This project helps machine learning engineers and researchers combine predictions from several smaller, specialized language models into one larger, more capable model. It takes outputs from multiple 'local' models trained on specific datasets and a 'global' model pretrained on broader data, then merges their knowledge. The result is a single, more robust language model that can perform tasks like sentiment analysis efficiently.
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Use this if you need to consolidate the expertise of multiple specialized natural language processing (NLP) models into a single, high-performing model, especially when computational resources for individual models are a concern.
Not ideal if you are looking for a pre-trained, ready-to-use NLP model without needing to combine outputs from existing smaller models or delve into the specifics of knowledge distillation techniques.
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Sep 15, 2022
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