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Source channel @githubtrending · Post #14974 · Jul 19

#cplusplus ik_llama.cpp is an improved version of llama.cpp that runs faster on CPUs and hybrid GPU/CPU setups. It supports many new advanced quantization methods, which help models use less memory and run more efficiently. It also offers better performance for special models like DeepSeek and MoE, with faster prompt processing and token generation. You can run it on various hardware, including Android, and it has features to control where model data is stored (CPU or GPU). This means you get quicker AI responses and can handle bigger or more complex models smoothly on your computer or device[2][1][4]. https://github.com/ikawrakow/ik_llama.cpp

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Co-Learning Center

@colearninguz · Post #12 · 12/27/2020, 07:29 AM

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Dasturlash doimiy ravishda oʻz ustida ishlash degani. Shuningdek, u toʻxtovsiz oʻrganishni ham talab etadi. Oʻrganish jarayonida kitobdan yaxshi koʻmakchi yoʻq, shunday emasmi? 🧑‍💻 “Clean Code: A Handbook of Agile Software Craftsmanship” Robert C. Martinʼning kitobi boʻlib, unda kodni tozalash, yozish va qayta tiklash boʻyicha batafsil, bosqichma-bosqich tushuntirishlar mavjud. Siz dasturiy taʼminotni ishlab chiqish loyihalarida SDLC'ning yetakchi shakllaridan biri boʻlgan Agile metodologiyasini gʻayrat bilan amalga oshira olasiz. Bundan tashqari, siz avvalgidan koʻra qatʼiyatli va intizomli dasturchi boʻlasiz. #CLC#Chitay#Coding_hazil_emas @colearninguz

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