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Source channel @githubtrending · Post #14815 · Jun 10

#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

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@githubtrending · Post #14788 · 06/05/2025, 12:00 AM

#cplusplus#avx#avx_512#avx_instructions#avx2#avx512#intrinsics#neon#simd#simd_instructions#simd_intrinsics#simd_library#simd_parallelism#simd_programming#sse42#wasm Highway is a C++ library that helps make software run faster and use less energy. It does this by using SIMD (Single Instruction, Multiple Data) instructions, which let the CPU perform the same operation on many pieces of data at once. This can make programs up to 10 times faster and reduce energy use by up to five times. Highway works on many different types of computers and is easy to use, making it a good choice for developers who want to improve their software's performance. https://github.com/google/highway