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소스 채널 @phpdevelopersuz · Post #2382 · 3월 15일

Dasturchilar uchun Google tomonidan Code Jam onlayn musobaqasi. Tanlov g'oliblariga pul mukofotlari topshiriladi Talablar — Tanlovda 18 yoshdan katta bo'lgan dasturchilik sohasiga qiziquvchi yoshlar qatnashishlari mumkin; — Dasturchilarning Google accountlarida o'z ism-shariflari, telefon nomerlari va qaysi davlatda yashashlari aniq va batafsil keltirib o'tishlari so'raladi; — Dastur ishchi tili ingliz tili ekanligi uchun shu tildan xabardor bo'lishi kerak (sertifikat shartmas). Foydali tomonlari — 1-raunddan 2-raundga o'tgan eng yaxshi 1000 ta dasturchi ichiga kirgan nomzodlarga Code Jam futbolkalari beriladi; — Code Jam musobaqasida oxirgi 5-bosqichiga yetib kelgan ishtirokchilar quyidagi miqdordagi pul mukofotlari bilan taqdirlanadilar: — 1-o'rin - $15 000; — 2-oʻrin — $2000; — 3-oʻrin — $1000; — 4-25-oʻrin — $100. Oxirgi muddat 03.04.2022 23:59 Batafsil https://grantgo.uz/go/56580 #tanlovlar#mukofot#AQSh

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GitHub Trends

@githubtrending · Post #15091 · 2025. 08. 24. AM 11:30

#python#comfyui#diffusion#flux#genai#mlsys#quantization Nunchaku is a fast and efficient engine that runs 4-bit neural networks using a special method called SVDQuant, which compresses models to use less memory and speed up processing by 2 to 5 times compared to older methods. It supports advanced AI models for tasks like high-quality text-to-image generation and image editing, working best on modern NVIDIA GPUs. You can easily install and use it with ComfyUI, and it has active community support on Slack, Discord, and WeChat. This means you can generate or edit images quickly with less computing power, saving time and resources. It also offers tutorials and example workflows to help you get started smoothly. https://github.com/nunchaku-tech/ComfyUI-nunchaku

GitHub Trends

@githubtrending · Post #15539 · 2026. 03. 05. AM 11:30

#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools. https://github.com/inclusionAI/AReaL