What Are Embeddings alternatives for AI agents.

A repository of code samples for Vector search capabilities in Azure AI Search.

Retrieval and Retrieval-augmented LLMs

Implementation of the node2vec algorithm.

A blazing fast inference solution for text embeddings models

Jupyter Notebooks to help you get hands-on with Pinecone vector databases

Easily compute clip embeddings and build a clip retrieval system with them

Fast State-of-the-Art Static Embeddings

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

Explore and interpret large embeddings in your browser with interactive visualization! 📍

100+ Chinese Word Vectors 上百种预训练中文词向量

Bringing BERT into modernity via both architecture changes and scaling

Open Source Semantic Search for your AI Agent

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool.

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.