본 블로그는 알리바바 클라우드의 PAI 서비스와 Elasticsearch 서비스를 활용하여 RAG LLM 챗봇을 만들 수 있는 가이드입니다.
Bagian kedua dari seri tiga bagian ini memperkenalkan PaaS dan menjelajahi cara menyebarkan layanan AI generatif yang bermanfaat dalam beberapa menit menggunakan PAI.
Phần thứ hai trong loạt bài gồm ba phần này giới thiệu PaaS và khám phá cách triển khai các dịch vụ AI tạo sinh hữu ích chỉ trong vài phút bằng cách sử dụng PAI.
この 3 部構成のシリーズの第 2 部では、PaaS を紹介し、PAI を使用して役に立つ生成 AI サービスを数分でデプロイする方法を探ります。
The second part of this three-part series introduces PaaS and explores how to deploy useful generative AI services in minutes using PAI.
This article uses llama-2-7b-chat as an example to describe how to use QuickStart to deploy a model as a service in Elastic Algorithm Service (EAS) and call the service.
This article describes how to quickly deploy a Llama 3 model and use the deployed web application in Elastic Algorithm Service (EAS) of Platform for AI (PAI).
This article describes how to deploy an LLM in EAS and call the model.
This article describes how to deploy a web application based on the open source model Tongyi Qianwen and perform model inference on the web page or using API operations in EAS of PAI.
This article describes how to deploy a Hugging Face model in PAI EAS.
This article describes how to deploy an AI video generation application, related inference services and answers to FAQ during the deployment.
This article describes how to deploy a Stable Diffusion model and use the deployed application to perform model inference and generate images.
Our ultimate purpose is to mount this OSS image dataset to the DSW instance and enable the usage of the dataset the same way I used in the standalone .
This article describes how to deploy a Llama 2 model or a fine-tuned model as a ChatLLM-WebUI application, start the web UI, and perform model inference by using API operations.
This article describes how to use Elastic Algorithm Service (EAS) of Platform for AI (AI) to deploy the Stable Diffusion (SD) API service and how to use SD APIs for model inference.
This article describes how to deploy the open source Kohya_ss and train a Low-Rank Adaptation (LoRA) model by using the Kohya_ss in the EAS of PAI.
This article describes how to use an image to deploy the Stable Diffusion model as a web application in EAS, perform model inference with web UI and generate images based on text prompts.
This article delves into the key features and functionalities of Alibaba Cloud's Platform for AI, exploring its capabilities from data preparation to model deployment.
This article introduces Alibaba Cloud PAI, a platform that combines AI capabilities with Langchain and LLM to revolutionize the field of Generative AI.
The model deployment section below has Elastic Algorithm Service (EAS) which houses the deployment models already available and acts as a platform to deploy the customized models created by the users.
