Popular GitHub Repositories for Text Embedding

[ACL 2023] One Embedder, Any Task: Instruction-Finetuned Text Embeddings

Codebase for RetroMAE and beyond.

Efficient LLM inference on Slurm clusters using vLLM.

a vector embedding database with multiple storage engines and AI embedding integrations

Simple script to compute CLIP-based scores given a DALL-e trained model.

Simple customizable evaluation for text retrieval performance of Sentence Transformers embedders on PDFs

Perform topic classification on news articles in several limited-labeled data regimes.

Simple script to re-rank images using OpenAI's CLIP https://github.com/openai/CLIP.

Flask API for generating text embeddings using OpenAI or sentence_transformers

Topic Embedding, Text Generation and Modeling using diffusion

PL-MTEB: Polish Massive Text Embedding Benchmark

Embedding a text to a vector by pre-trained BERT word embeddings and pooling layers, for the pur[ose of text similarity measuring

Using Semantic Kernel to obtain answer from a PDF document, with embeddings stored in Redis and HuggingFace to create embeddings.

Mind-X is my intelligent alter ego that understands me the best. It assists with and resolves my bothersome tasks, growing in real-time as a next-generation PersonAI system.

Fast text embedding service

This code repo demonstrates how to use the word embedding model from Azure OpenAI Service to perform a semantic search on a grocery store dataset. This enhanced/completed version used Streamlit to build a web user experience to semantic search and display the most relevant items

This code repo demonstrates how to use the word embedding model from Azure OpenAI Service to perform a semantic search on a grocery store dataset.

Facebook Chat Bot with Embeddings. A customizable bot for Facebook Messenger using text embeddings and XGBoost for automated responses. Easily adaptable to various industries and workflows.

In this project text embedding is used to convert a set of text information about start-ups into vectors. Then these vectors are used to add context to a query, assisting the completion model in answering a query.

CLI that helps with docs splitting, embedding and exposing them in a seamless manner