#Sentence-transformers
Showing 28 of 28 repositories tagged #sentence-transformers, ranked by stars
A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
Fast State-of-the-Art Static Embeddings
Efficient Retrieval Augmentation and Generation Framework
On-premises conversational RAG with configurable containers
An editing tool that uses AI to transcribe, understand content and search for anything in your footage, integrated with ChatGPT and other AI models
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
Local first semantic code search and chat | Leverage custom copilots with fine-tuning datasets from code in Alpaca, Conversational, Completion and Instruction format
Local-first persistent memory for AI coding agents (Claude Code, Cursor, Codex) over MCP. Decisions, lessons and facts live in one SQLite file on your disk. Offline, multilingual.
Making BERT stretchy. Semantic Elasticsearch with Sentence Transformers
Local-GenAI-Search is a generative search engine based on Llama 3, langchain and qdrant that answers questions based on your local files
Browse the top 10,000 packages on PyPI with the help of vector embeddings
Organize and classify files based on their content using NLP
Similarity detection for Github Issues + AI code reviews
Local-first AI memory archive. Import ChatGPT, Claude, and Grok exports, generate semantic embeddings, and search via MCP server. Zero cloud, zero cost.
Python library for generating ambient music from text descriptions. No GPU required. Turn text into sound with a single line of code.
Learn how to talk to Django as any human should -- e.g. Semantic Search and Text-to-SQL.
Sentence-Transformers Information Retrieval example on Chinese
LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.
Train linear embedding adapters with triplet loss to align retrieval embeddings with your queries (RAG).
DocFinder is a local-first indexing and searching documents using semantic embeddings stored in SQLite. Everything runs on your machine, no external services required.
Semantic search knowledge base for MCP-enabled AI assistants. Index local files or GitHub repos, query with natural language. Built on LanceDB vector storage. Works with Claude Desktop, Cursor, and other MCP clients.
The AI-Powered Healthcare Intelligence Network is an AI-driven system offering disease prediction, drug recommendations, heart disease risk assessment, and an AI medical chatbot. Using ML, NLP, and LLMs, it provides accurate diagnoses, insights, and recommendations, enhancing healthcare accessibility, efficiency, and decision-making .
This is a RAG implementation using Open Source stack. BioMistral 7B has been used to build this app along with PubMedBert as an embedding model, Qdrant as a self hosted Vector DB, and Langchain & Llama CPP as an orchestration frameworks.
Match celebrity users with their respective tweets by making use of Semantic Textual Similarity on over 900+ celebrity users' 2.5 million+ crawled tweets utilizing SBERT, streamlit, tweepy and FastAPI
Data pipelines for AI applications
Taxonomy Completion with Embedding Quantization and an LLM-based Pipeline: A Case Study in Computational Linguistics