The all-in-one solution for RAG. Build, scale, and deploy state of the art Retrieval-Augmented Generation applications
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Updated
Nov 9, 2024 - Python
The all-in-one solution for RAG. Build, scale, and deploy state of the art Retrieval-Augmented Generation applications
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 based on RQ-VAE 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 (wyu1@nd.edu). 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.
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
Retrieval based TF-IDF English and Burmese bilingual chatbot for Covid-19 domain
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