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Source channel @githubtrending · Post #14636 · Apr 27

#powershell#automated#bloatware#bloatware_removal#cleanup#debloat#debloater#interactive#optimize#powershell#powershell_script#privacy#ps1#registry_tweaks#tweaks#windows#windows_10#windows_11#windows_11_debloat#windows10#windows11 Win11Debloat is a free PowerShell script that quickly removes pre-installed Windows bloatware like TikTok, Xbox Game Bar, and Copilot while disabling ads, telemetry, and intrusive features. It simplifies tasks like restoring the classic right-click menu, hiding duplicate drives in File Explorer, and removing taskbar clutter, saving you from manually adjusting settings. The script is safe, reversible, and improves your experience by eliminating unnecessary background processes and distractions, making Windows cleaner and more focused. https://github.com/Raphire/Win11Debloat

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Илья AGI TV 🤖

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

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

#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