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Source channel @githubtrending · Post #15329 · Dec 13

#typescript#browser#chrome#chrome_devtools#debugging#devtools#mcp#mcp_server#puppeteer Chrome DevTools MCP lets your AI coding tools like Gemini, Claude, or Cursor control a live Chrome browser for automation, debugging, and performance checks. Install it easily with npx chrome-devtools-mcp@latest in your MCP config, then prompt "Check performance of a site" to auto-record traces, take screenshots, analyze networks, and fix issues reliably. This benefits you by making AI smarter at web coding—verifying changes in real-time, spotting bugs fast, and boosting site speed without manual work. https://github.com/ChromeDevTools/chrome-devtools-mcp

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@githubtrending · Post #14815 · 06/10/2025, 11:30 AM

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm