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Source channel @githubtrending · Post #14727 · May 20

#javascript#cloud#cloud_os#cloud_storage#desktop#desktop_environment#dropbox#good_first_issue#gui#javascript#nas#open_source#operating_system#os#osjs#puter#remote_desktop#storage#web_desktop#web_os#webtop Puter is a privacy-first personal cloud that lets you store files, apps, and games securely. You can access everything from anywhere at any time, making it very convenient. It's like a personal computer in the cloud, and you can use it on any device—Windows, Mac, Linux, or even your smartphone. Puter also helps you organize your work and entertainment by allowing multiple virtual desktops. This means you can keep different tasks separate but easily accessible, which helps you work more efficiently. Plus, it's open-source, so you can customize it to fit your needs. https://github.com/HeyPuter/puter

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Илья AGI TV 🤖

@ilia_plasma · Post #148 · 10/08/2023, 12:16 PM

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Пока весь мир ждет доступа к новой модели со зрением GPT-4V(ision), опенсорс команда (пара азитов со степенью PhD из американских вузов) уже выпустили свой аналог и бесплатную версию #LLaVA (Large Language and Vision Assistant), которая выдает результат (не) хуже GPT4V и может работать локально. Вот такая скорость развития и конкуренции в этом новом #AI рынке. 🧠LLava - вебсайт 📄WhitePaper 🧬Github code 🔋Demo для потестить на своих дикпиках 🦒Colab (для запуска у себя на серваке)

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@githubtrending · Post #15600 · 04/04/2026, 11:30 AM

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#python#apple_silicon#florence2#idefics#llava#llm#local_ai#mlx#molmo#paligemma#pixtral#vision_framework#vision_language_model#vision_transformer MLX-VLM lets you run, chat with, and fine-tune Vision Language Models (VLMs) plus audio/video models on your Mac using MLX—install easily with `pip install -U mlx-vlm`. Use CLI for quick text/image/audio generation (e.g., `mlx_vlm.generate --model ... --image photo.jpg`), Gradio UI for chats, Python scripts, or a FastAPI server with OpenAI-compatible endpoints supporting multi-images/videos. Features like TurboQuant cut KV cache memory by 76%, and LoRA/QLoRA fine-tuning works on consumer hardware. You benefit by experimenting with powerful multimodal AI locally—fast, memory-efficient, no cloud costs, perfect for Mac users tweaking models affordably. https://github.com/Blaizzy/mlx-vlm

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#python #apple_silicon #florence2 #idefics #llava #llm #local_ai #mlx #molmo #paligemma #pixtral #vision_framework #vision_language_model #vision_transformer