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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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🟣 2024 🟣 V. 11 🟣 Issue 4 🟣 Art. 202411411 🟣 Article 🟣 Опубликована новая статья 📜 Impact of calcium and copper co-doping on the oxygen transport of layered nickelates: a case study of Pr1.6Ca0.4Ni1–yCuyO4+δ and a comparative analysis 👩‍🎓👨‍🎓 V. Sadykov (https://orcid.org/0000-0003-2404-0325), N. Eremeev (https://orcid.org/0000-0002-3494-2771), E. Sadovskaya, T. Zhulanova (https://orcid.org/0000-0002-8009-4398), S. Pikalov (https://orcid.org/0000-0001-6292-0468), Y. Fedorova, E. Pikalova (https://orcid.org/0000-0001-8176-9417) 🏛 Federal Research Center Boreskov Institute of Catalysis SB RAS https://en.catalysis.ru 🏛 Institute of High-Temperature Electrochemistry UB RAS, https://ihte.ru 🏛 Ural Federal University, https://urfu.ru/en Institute of Metallurgy UB RAS, http://www.imeturan.ru 📚#SOFCs#SOECs#layered#nickelates#oxygen#transport#isotope#exchange 🔗https://doi.org/10.15826/chimtech.2024.11.4.11 https://journals.urfu.ru/index.php/chimtech/article/view/8073