The open source Firebase alternative. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications.
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Updated
Nov 8, 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).
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