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Source channel @githubtrending · Post #14949 · Jul 12

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#jupyter_notebook#darknet#pytorch#scaled_yolov4#yolor#yolov3#yolov4#yolov7 YOLOv7 is a powerful tool for detecting objects in images and videos. It is fast, accurate, and can work well on devices with limited power, making it useful for real-time applications like self-driving cars and surveillance systems. YOLOv7 uses advanced techniques like Feature Pyramid Networks to detect objects of different sizes and can handle complex scenes with overlapping objects. This makes it beneficial for users who need quick and precise object detection in various environments. https://github.com/WongKinYiu/yolov7

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Machinelearning

@ai_machinelearning_big_data · Post #8255 · 08/12/2025, 02:32 PM

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🚀Jan-v1: локальная 4B-модель для веба — опенсорсная альтернатива Perplexity Pro 📌Что умеет - SimpleQA: 91% точности, чуть выше Perplexity Pro — и всё это полностью локально. - Сценарии: быстрый веб-поиск и глубокое исследование (Deep Research). Из чего сделана - Базируется на Qwen3-4B-Thinking (контекст до 256k), дообучена в Jan на рассуждение и работу с инструментами. Где запускать - Jan, llama.cpp или vLLM. Как включить поиск в Jan - Settings → Experimental Features → On - Settings → MCP Servers → включите поисковый MCP (например, Serper) Модели - Jan-v1-4B: https://huggingface.co/janhq/Jan-v1-4B - Jan-v1-4B-GGUF: https://huggingface.co/janhq/Jan-v1-4B-GGUF @ai_machinelearning_big_data #ai#ml#local#Qwen#Jan

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