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#

embedding-models

Here are 305 public repositories matching this topic...

MineContext is your proactive context-aware AI partner(Context-Engineering+ChatGPT Pulse)

  • UpdatedDec 18, 2025
  • Python

A curated list of awesome embedding models tutorials, projects and communities.

  • UpdatedApr 7, 2019
  • Jupyter Notebook

Generative Representational Instruction Tuning

  • UpdatedJun 25, 2025
  • Jupyter Notebook

Python library for knowledge graph embedding and representation learning.

  • UpdatedApr 21, 2021
  • Python

OpenL3: Open-source deep audio and image embeddings

  • UpdatedJun 17, 2023
  • Jupyter Notebook

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.

  • UpdatedSep 23, 2025
  • Jupyter Notebook

Implementations of Embedding-based methods for Knowledge Base Completion tasks

  • UpdatedNov 7, 2020
  • Python
image_search_engine

Image search engine

  • UpdatedNov 22, 2022
  • Python

A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.

  • UpdatedMay 29, 2024
  • TypeScript

Neural Code Comprehension: A Learnable Representation of Code Semantics

  • UpdatedNov 22, 2024
  • Python

Official code for ACL2025 "🔍 Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models"

  • UpdatedJun 26, 2025
  • JavaScript
webvectors

Web-ify your word2vec: framework to serve distributional semantic models online

  • UpdatedFeb 20, 2025
  • Python

Optimize Document Retrieval with Fine-Tuned KnowledgeBases

  • UpdatedNov 5, 2025
  • Python

Train an adapter for any embedding model in under a minute

  • UpdatedApr 9, 2025
  • Python

ToR[e]cSys is a PyTorch Framework to implement recommendation system algorithms, including but not limited to click-through-rate (CTR) prediction, learning-to-ranking (LTR), and Matrix/Tensor Embedding. The project objective is to develop an ecosystem to experiment, share, reproduce, and deploy in real-world in a smooth and easy way.

  • UpdatedApr 8, 2022
  • Python

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