The most advanced AI retrieval system. Containerized, Retrieval-Augmented Generation (RAG) with a RESTful API.
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Updated
Dec 26, 2024 - Python
The most advanced AI retrieval system. Containerized, Retrieval-Augmented Generation (RAG) with a RESTful API.
A curated list of retrieval-augmented generation (RAG) in large language models
[EMNLP 2024] The official GitHub repo for the survey paper "Knowledge Conflicts for LLMs: A Survey"
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
The sources codes of the DR-BERT model and baselines
简版文本对话/问答系统
Tracked Vehicle Retrieval by NL Challenge in the 2023 AI City Challenge.
Knowledge pills on Neural Search
js client for R2R: production-ready RAG engine with a sh*t ton of features.
Author: Wenhao Yu ([email protected]). EMNLP'20. Transfer Learning for Technical Question Answering.
RAG system with real-time news scraping built using mixtral-8x7b, ChromaDB, bart summarizer
vitrivr's next-generation retrieval engine. It is capable of extracting and retrieving a wider range of multimedia objects such as audio, video, images or 3d models.
Large-scale user portarit ranking and generation augmented retrieval systems.
REST API for computing cross-modal similarity between images and text using the ColPaLI vision-language model
Official github repository of Semantic Labels-Aware Transformer Model for Searching over a Large Collection of Lecture-Slides WACV 2023
Various Indexing and Query Based Retrieval Models and Page-rank Algorithm in Python 3.0
Combine fIne-tuning and retrieval-augmented generation
using feature maximisation for summarizing scientifc documents
1401/Spring/InformationRetrieval/g5+23
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