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Source channel @pushgoodcloud · Post #607 · 11月30日

#Lantau#大屿山 之前购买过的,可以联系 @ljfxz 退款,直接发机场邮箱给他 剩余价值退款按照( 剩余时长*时长单价)+(剩余流量*流量单价)的形式退款 流量单价=套餐价格*0.8/套餐流量总数 时长单价=套餐价格*0.2/套餐时长总数 例如轻量套餐价格为9元,流量为80G,时长为30天。那天数单价为(0.2*9)/30,流量单价为(0.8*9)/80。 此时轻量用户还剩10天,流量还有70G,那退款为10*[(0.2*9)/30] + 70*[(0.8*9)/80] 注* 充了流量的钱也可退

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

#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