#Embedding-models
Showing 15 of 15 repositories tagged #embedding-models, ranked by stars
MineContext is your proactive context-aware AI partner（Context-Engineering+ChatGPT Pulse）
A curated list of awesome embedding models tutorials, projects and communities.
Generative Representational Instruction Tuning
This repository provides programs to build Retrieval Augmented Generation (RAG) code for Generative AI with LlamaIndex, Deep Lake, and Pinecone leveraging the power of OpenAI and Hugging Face models for generation and evaluation.
OpenL3: Open-source deep audio and image embeddings
Program that lets you ask questions about your documents, audio, and video files.
Word Embeddings for Information Retrieval
GenAI/RAG Optimizer and Toolkit for experimentation using Oracle Database AI Vector Search and NL2SQL
🐸 KERMIT - A lightweight library to encode and interpret Universal Syntactic Embeddings
AI Engineering Specially Topics- Agentic AI & GenAI Explanation
Code and resources showcasing the Retrieval-Augmented Generation (RAG) technique, a solution for enhancing data freshness in Large Language Models (LLMs). Incorporate up-to-date external knowledge into LLM-generated responses. Additionally, this repository includes a Gradio-based user interface for seamless model deployment.
Query Only Linear Adapter Training for Fine Tuned Embedding Model Query Representation
Fine-tuning black-box OpenAI embedding models
Built in SenseTime in 2024. Training and evaluation code of EGTLM model. A model that can do text generation and text embedding tasks simultaneously.
This repository contains samples for fine-tuning embedding models using Amazon SageMaker. Embedding models are useful for tasks such as semantic similarity, text clustering, and information retrieval. Fine-tuning these models on your specific domain data can greatly improve their performance.