All-in-One: Text Embedding, Retrieval, Rerank and RAG
-
Updated
Jun 5, 2024 - Python
All-in-One: Text Embedding, Retrieval, Rerank and RAG
🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.
Infinity is a high-throughput, low-latency REST API for serving vector embeddings, supporting a wide range of text-embedding models and frameworks.
Evaluating state-of-the-art embedding models with domain-specific instructions to improve semantic representation and enhance explainability in semantic search.
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.
Go module for fetching embeddings from embeddings providers
Train Models Contrastively in Pytorch
PDF Reader App with integrated chat, read and discuss in real time.
A Python-based search engine for OpenAI's ChatGPT conversation history, enabling efficient semantic search and interactive engagement with archived chats using text embeddings
This repository deals with vector database preparation.
Interactive tree-maps with SBERT & Hierarchical Clustering (HAC)
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.
A news insight synthesizer designed to cut the noise out of media consumption (using LLMs & text-embeddings)
This app allows users to search for products by either entering text or uploading an image, and retrieves relevant products from a database
Uses NLP & LSTM to detect insincere Quora Questions
Open Source Text Embedding Models with OpenAI Compatible API
Topic Embedding, Text Generation and Modeling using diffusion
Large language models offer new opportunities for processing and generating text. I used text embeddings, clustering, and the ChatGPT API to examine the reasons for startup failure.
Dive into the world of text embeddings. This course will guide you through leveraging text embeddings to enhance various natural language processing (NLP) tasks.
A text embedding viewer for the Jupyter environment
Add a description, image, and links to the text-embeddings topic page so that developers can more easily learn about it.
To associate your repository with the text-embeddings topic, visit your repo's landing page and select "manage topics."