Introducing the Quaterion: a framework for fine-tuning similarity learning models

We’re happy to share the result of the work we’ve been into during the last months - Quaterion. It is a framework for fine-tuning similarity learning models that streamlines the training process to make it significantly faster and cost-efficient.

To develop Quaterion, we utilized PyTorch Lightning, leveraging a high-performing AI research approach to constructing training loops for ML models.

quaterion

This framework empowers vector search solutions, such as semantic search, anomaly detection, and others, by advanced coaching mechanism, specially designed head layers for pre-trained models, and high flexibility in terms of customization according to large-scale training pipelines and other features.

Here you can read why similarity learning is preferable to the traditional machine learning approach and how Quaterion can help benefit https://quaterion.qdrant.tech/getting_started/why_quaterion.html#why-quaterion   

A quick start with Quaterion:https://quaterion.qdrant.tech/getting_started/quick_start.html

And try it and give us a star on GitHub :) https://github.com/qdrant/quaterion