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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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@githubtrending · Post #14898 · 07/02/2025, 01:30 PM

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#javascript#3d#augmented_reality#canvas#html5#javascript#svg#virtual_reality#webaudio#webgl#webgl2#webgpu#webxr Three.js is a powerful and easy-to-use JavaScript library that helps you create 3D graphics and animations on the web with much less code than using WebGL directly. It handles complex tasks like rendering and math calculations, so you can focus on designing your 3D scenes. It supports WebGL and WebGPU, with additional options like SVG and CSS3D. Three.js has excellent documentation, many examples, and a large, active community that provides support and updates. This makes it ideal for quickly building interactive 3D content that works across browsers, improving your web projects with engaging visuals and smooth performance[1][3][5]. https://github.com/mrdoob/three.js

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