Hugging Face Dataset Ingestion

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Load Hugging Face Datasets into Qdrant

Hugging Face provides a platform for sharing and using ML models and datasets. Qdrant also publishes datasets along with the embeddings that you can use to practice with Qdrant and build your applications based on semantic search. Please let us know if you’d like to see a specific dataset!

arxiv-titles-instructorxl-embeddings

This dataset contains embeddings generated from the paper titles only. Each vector has a payload with the title used to create it, along with the DOI (Digital Object Identifier).

Semantic Search 101

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Build a Semantic Search Engine in 5 Minutes

Time: 5 - 15 min	Level: Beginner

Overview

If you are new to vector databases, this tutorial is for you. In 5 minutes you will build a semantic search engine for science fiction books. After you set it up, you will ask the engine about an impending alien threat. Your creation will recommend books as preparation for a potential space attack.

Basics on Qdrant - Vector Database

Hugging Face Dataset Ingestion

Load Hugging Face Datasets into Qdrant

arxiv-titles-instructorxl-embeddings

Semantic Search 101

Build a Semantic Search Engine in 5 Minutes

Overview