Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali

DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks

Train Models Contrastively in Pytorch

🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.

A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.

Open Source Text Embedding Models with OpenAI Compatible API

Go module for fetching embeddings from embeddings providers

Interactive tree-maps with SBERT & Hierarchical Clustering (HAC)

Code implementation for our ICPR, 2020 paper titled "Improving Word Recognition using Multiple Hypotheses and Deep Embeddings"

A text embedding viewer for the Jupyter environment

A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store

Flask API for generating text embeddings using OpenAI or sentence_transformers

Topic Embedding, Text Generation and Modeling using diffusion

I have improved the demo by using Azure OpenAI’s Embedding model (text-embedding-ada-002), which has a powerful word embedding capability. This model can also vectorize product key phrases and recommend products based on cosine similarity, but with better results. You can find the updated repo here.

Semantic similarity via text embeddings in Elixir - powered by SentenceTransformers by SBert.net

KRLawGPT : Generative Pre-trained Transformer for producing Korean Legal Text

Sentiment Analysis on the Amazon Reviews Dataset using BERT-based transfer learning approach.

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.

Easy embeddings for LLMs like gpt-3.5-turbo and gpt-4 using text-embedding-ada-002

Graph Attention Networks for Entity Summarization is the model that applies deep learning on graphs and ensemble learning on entity summarization tasks.