tiny-gte “Tiny, yet powerful, it is small in size but packs a lot of power.”

let’s explore this applications with txtai and other workflow with some notes and future directions
Author

kareem

Published

October 21, 2023

Table of contents

#definition : This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. It is distilled from thenlper/gte-small, with comparable (slightly worse) performance at around half the size.

Details

  • It’s around ~45MB very small compared to other models like MiniLM-L6-V2 which is equal to ~80 MB
  • Embedding vector size 384d
  • BERT based
  • Distilied from thenlper/gte-small,

Notice about using small size

Use Cases

Todo

    1. Add the link of it into the this blog
  2. Explain fastembed
  3. Make comparison between tiny-gte and small gte
  4. Add the small-gte-4096 comparison

References

  • https://huggingface.co/TaylorAI/gte-tiny
  • https://www.linkedin.com/posts/prithivirajdamodaran_%3F%3F%3F%3F-%3F%3F%3F%3F-%3F%3F%3F%3F%3F-%3F%3F%3F%3F-activity-7120279840569597952-iwc-/?utm_source=share&utm_medium=member_desktop