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

Qdrant team shared the result of the work they’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, Qdrant team utilized PyTorch Lightning, leveraging a high-performing AI research approach to constructing training loops for ML models.

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

Quaterion on GitHub: https://github.com/qdrant/quaterion