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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 #14774 · 06/01/2025, 12:00 PM

#cplusplus#3mf#android#asset_pipeline#assets#assimp#c_plus_plus#collada#dae#fbx#fbx_exporter#game_development#gamedev_tool#gamedevelopment#gltf#gltf2#ifc#patreon#python#stl The Open Asset Import Library (Assimp) is a tool that helps load many different 3D file formats into a common format. It supports over 40 formats for importing and several for exporting. Assimp works on various platforms like Windows, macOS, Linux, Android, and iOS. It also provides tools to improve the 3D models, such as fixing errors and making them look better. This library is useful for developers because it simplifies working with different 3D file types, making it easier to create and manage 3D content across different systems. https://github.com/assimp/assimp