【关于使用RAG模式(Retrieval-Augmented Generation)的应用和资源的信息,包括关于RAG技术的综述,以及一些GitHub库和企业级应用的链接,这些应用使用RAG模型来增强自然语言处理和信息检索能力】'Awesome-LLM-RAG-Application - the resources about the application based on LLM with RAG pattern' GitHub: github.com/lizhe...
检索增强生成(RAG, Retrieval-Augmented Generation) 最早由Lewis等人于2020引入,将预先训练的检索器与预先训练的seq2seq模型(生成器)相结合,并进行端到端的微调,以更可解释和模块化的方式获取知识。 在大型模型出现之前,RAG主要专注于端到端模型的直接优化。在检索端进行密集检索,例如Karpukhin等人使用基于向量的密集...
NIPS’15, page 190–198, Cambridge, MA, USA, 2015. MIT Press. URLhttps://papers.nips.cc/paper/5857-inferring-algorithmic-patterns-with-stack-augmented-recurrent-nets.
You can use foundation models in IBM watsonx.ai to generate factually accurate output that is grounded in information in a knowledge base by applying the retrieval-augmented generation pattern.
This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-4o-mini), and Azure AI Search for data indexing and retrieval. ...
Advances in artificial intelligence and machine learning help companies improve their customer experiences, such as the Retrieval Augmented Generation (RAG) pattern. RAG empowers businesses to create ChatGPT-like interactions tailored to their specific d
Retrieval-Augmented Generation (RAG) is a design pattern that combines a pretrained Large Language Model (LLM) like ChatGPT with an external data retrieval system to generate an enhanced response incorporating new data outside of the original training data. Adding an information retrieval sy...
LLM之RAG:《Retrieval-Augmented Generation for Large Language Models: A Survey大型语言模型的检索增强生成研究综述》翻译与解读 导读:这篇论文主要围绕信息检索增强生成(Retrieval Augmented Generation,简称RAG)技术进行概述和分析。 背景痛点: >> 大语言模型(LLM)在处理知识密集型任务和回答离线知识更丰富的问题时面临...
A common scenario is to use LLMs to engage in conversations using your own data through the Retrieval Augmented Generation (RAG) pattern. This pattern lets you use the reasoning abilities of LLMs to generate responses based on your specific data without fine-tuning the model. It facilitates...
Sep 25, 2024 Retrieval-augmented generation (RAG) is a powerful Generative AI implementation pattern that enhances generative models by incorporating corporate information by way of data retrieval mechanisms without additional model training.RAG lets you optimize the output of a large language model (LLM...