The open source Firebase alternative. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.
-
Updated
Nov 9, 2024 - TypeScript
The open source Firebase alternative. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.
The Memory layer for your AI apps
the AI-native open-source embedding database
100+ Chinese Word Vectors 上百种预训练中文词向量
Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Retrieval and Retrieval-augmented LLMs
Postgres with GPUs for ML/AI apps.
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
Java version of LangChain
text2vec, text to vector. 文本向量表征工具,把文本转化为向量矩阵,实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型,开箱即用。
Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..
A library for transfer learning by reusing parts of TensorFlow models.
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
A python library for self-supervised learning on images.
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
A blazing fast inference solution for text embeddings models
An app to interact privately with your documents using the power of GPT, 100% privately, no data leaks
Chat with your notes & see links to related content with AI embeddings. Use local models or 100+ via APIs like Claude, Gemini, ChatGPT & Llama 3
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).
Add a description, image, and links to the embeddings topic page so that developers can more easily learn about it.
To associate your repository with the embeddings topic, visit your repo's landing page and select "manage topics."