Code Qwen AI Challenge – Algorithm Track Overview

Code Qwen AI Challenge - Algorithm Track Overview

Introduction Competition Link: Code Qwen AI Challenge – Algorithm Track_Algorithm Competition_Questions and Data_Tianchi Competition – Data and Questions from Alibaba Cloud Tianchi Code is one of the high-quality languages created by humans, replacing the diverse natural language through high abstraction, ultimately converting to specific programs to complete tasks for humans. It possesses advantages such as … Read more

Deploying Open Source Large Models Locally with Ollama

Deploying Open Source Large Models Locally with Ollama

ClickFollowWeChat Official Account, “Technical Insights” for Timely Updates! Introduction If you want to deploy and run an open-source large model on localhost, you can try Ollama. In this article, we will deploy Ollama and call the large model via API. Installation Ollama provides two development packages for Python and JavaScript, which are quite friendly for … Read more

Creating a Web Q&A Bot: Implementing RAG with Ollama and Scrapers

Creating a Web Q&A Bot: Implementing RAG with Ollama and Scrapers

Recently, the official Ollama released its Python tool library. This article introduces a guide to integrating Ollama into Python, showcasing how developers can easily utilize AI capabilities. The previous article discussed how to deploy Ollama’s large model. This time, we will expand on that foundation to create a web Q&A bot. Integrating the large model … Read more

Quickly Deploy Local Open Source Large Language Models Using Ollama

Quickly Deploy Local Open Source Large Language Models Using Ollama

If you’re starting to explore how to test open source large language models (LLM) with Generative AI for the first time, the overwhelming amount of information can be daunting. There is a lot of fragmented information from various sources on the internet, making it difficult to quickly start a project. The goal of this article … Read more

Introduction to Using LM Studio for Local LLM Applications

Introduction to Using LM Studio for Local LLM Applications

LM Studio is the simplest way to support local open-source large language models. It is plug-and-play, requires no coding, is very simple, and has a beautiful interface. Today, I will introduce this application. 1. What Can LM Studio Do? 🤖 Run LLM completely offline on a laptop 👾 Use models via in-app chat UI or … Read more

Ollama: Deploying Open Source Large Models Locally

Ollama: Deploying Open Source Large Models Locally

Click 01 Muggle Society Follow our public account, never get lost in AI learning Have you ever considered running open-source LLM locally? Do you have to manually download large model files? Are you struggling to build an API for your local model? Have you tried managing multiple models locally? I guess you have thought about … Read more

Automating Programming in VsCode with Cline and Deepseek

Automating Programming in VsCode with Cline and Deepseek

Have you heard of the tool Cursor? It’s like a combination of AI and VsCode. By binding APIs from large models like ChatGPT and Claude, you can achieve conversational self-programming, allowing you to develop a software application with just a casual chat. However, Cursor is limited by foreign networks, making it inaccessible for users in … Read more

Configuring DeepSeek for Automatic Programming in VS Code

Configuring DeepSeek for Automatic Programming in VS Code

On Windows, after configuring the DeepSeek large model in VS Code with Cline, the automatic programming attempt started. After the prompt was completed, there was almost no intervention throughout the process, and the project ran successfully on its own: Prompt: ### **Project: MP4 Video Upload and Online Playback Web Application** ### Architecture Requirements: Based on … Read more

Integrating DeepSeek with VSCode

Integrating DeepSeek with VSCode

1. DeepSeek is a Python library Install the library First, ensure your Python environment is properly configured (you can do this in VSCode by creating a virtual environment, etc.). Use pip install deepseek – your – specific – version (if there are specific version requirements) to install the DeepSeek library. Import and use in your … Read more