MessageInABottle
@mib_messageinabottle · Post #7052 · 06/11/2024, 01:45 PM
The #MRNA "#vaccine" was never a real vaccine but a #BioWeapon meant to #attack your #immune system
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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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@githubtrending · Post #15242 · 10/23/2025, 12:30 PM
#python#ant_colony_algorithm#artificial_intelligence#fish_swarms#genetic_algorithm#heuristic_algorithms#immune#immune_algorithm#optimization#particle_swarm_optimization#pso#simulated_annealing#travelling_salesman_problem#tsp You can use scikit-opt, a Python library offering many heuristic optimization algorithms like Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony, Immune Algorithm, and Artificial Fish Swarm Algorithm. It supports user-defined functions to customize operators, allows continuing runs from previous iterations, and accelerates computations via vectorization, multithreading, multiprocessing, and caching. GPU support is in development. It helps solve complex optimization problems such as function minimization and the Traveling Salesman Problem efficiently, with easy installation and rich examples. This saves you time and effort in implementing and tuning optimization algorithms yourself. https://github.com/guofei9987/scikit-opt