AI Model Tool Payment channels available in over 200 countries and regions, please choose! Cohere is a large language model platform focused on building top-notch AI products, primarily aimed at enterprise users and developers, especially those in need of efficient, flexible, and secure language AI solutions for B-end clients. Below is a detailed introduction to … Read more
Getting Started with Mistral: An Introduction The open-source Mixtral 8x7B model launched by Mistral adopts a “Mixture of Experts” (MoE) architecture. Unlike traditional Transformers, the MoE model incorporates multiple expert feedforward networks (this model has 8), and during inference, a gating network is responsible for selecting two experts to work. This setup allows MoE to … Read more
In this article, we will learn how to leverage Llama-3 to implement an advanced RAG with a fully local infrastructure.This article provides a firsthand guide for the first day of implementing advanced RAG. ◆Introduction: In this article, we will create an advanced RAG that will answer user queries based on research papers provided as input … Read more
Compiled by | Yan Zheng Data & AI entrepreneur, investor Oliver Molander recently joked in a LinkedIn post: “If you had asked AI experts what LLMs were before the launch of ChatGPT in 2022, many might have answered that it’s a law degree.” He added that many people find it hard to accept that AI … Read more
Click the bottom “Read Original” to browse the detailed content of “CCF Digital Focus” Issue 48 Editor’s Note Large language models (LLMs) still face many challenges when dealing with domain-specific or knowledge-intensive tasks, such as generating hallucinations, outdated knowledge, and opaque, untraceable reasoning processes. Retrieval-Augmented Generation (RAG) technology has emerged to address these issues. RAG … Read more
This article introduces a practical project that uses LangGraph to develop a RAG research multi-agent tool. This tool is designed to solve complex problems that require multiple sources and iterative steps to arrive at a final answer. It employs hybrid search and Cohere reordering steps to retrieve documents, and also includes a self-correction mechanism, including … Read more
https://txt.cohere.com/command-r/ https://huggingface.co/CohereForAI/c4ai-command-r-v01 1. RAG Performance On multiple datasets, it far exceeds the Mixtral MoE model. By using their own embeddings and reranking, it significantly outperforms open-source models. 2. Tool Capabilities The tool capabilities are slightly better than Mixtral and significantly outperform GPT-3.5. 3. Multilingual Capabilities Supports English, French, Spanish, Italian, German, Brazilian Portuguese, Japanese, Korean, … Read more
Project Introduction Cohere is an open-source toolkit for developing RAG applications, which can be deployed to Microsoft Azure with one click or run locally. Building and Running Locally Clone the repository and run make setup Configure the model according to the instructions – AWS Sagemaker, Azure, or the Cohere platform. This can also be accomplished … Read more
1. Overview The retriever is a part of the query engine, responsible for obtaining the most relevant context based on user queries (or chat messages). It can be built on existing indexes but can also be defined independently. It serves as a key building block for query engines (and chat engines) to retrieve relevant context. … Read more
LlamaIndex is a simple and flexible data framework that connects custom data sources with large language models. LlamaIndex provides comprehensive support for RAG. Advanced RAG (Retrieval-Augmented Generation) techniques can be modeled using a composable hierarchical abstraction. The retrieved text can be linked to the following elements: Retriever Text Pipeline Query Engine The retrieval of RAG … Read more