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Source channel @githubtrending · Post #15284 · Nov 9

#other Kimi K2 is a powerful AI language model with 1 trillion parameters, designed to understand very long texts and perform complex tasks like coding, reasoning, and using tools autonomously. It excels at writing and debugging code, solving math and science problems, and managing multi-step workflows by calling external tools or APIs automatically. You can access it via an easy-to-use API or deploy it on popular platforms. This means you get a smart assistant that not only answers questions but also acts to complete tasks, making your work faster and more efficient, especially for coding and research projects. https://github.com/MoonshotAI/Kimi-K2

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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