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Source channel @githubtrending · Post #14918 · Jul 6

#html#documentation#hacktoberfest#hass#hassio#home_assistant#jekyll You can set up and contribute to the Home Assistant website easily by following the developer documentation, which explains how to edit and preview the site locally using simple commands. This helps you see your changes live on your computer before sharing them. There are also tools to speed up website updates by temporarily hiding blog posts you’re not working on, making the process faster. This setup benefits you by making it straightforward to improve the site, test changes quickly, and manage content efficiently without delays. It’s designed to support smooth collaboration and faster website maintenance. https://github.com/home-assistant/home-assistant.io

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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