只要三個簡單步驟，就能在 Intel CPU 上運行 VLM 視覺語言模型
Original: Get your VLM running in 3 simple steps on Intel CPUs
Visual Language Models (VLMs) combine computer vision with natural language processing, enabling complex tasks such as image captioning and…
Hugging Face 介紹如何利用 OpenVINO 在 Intel CPU 上優化並運行視覺語言模型（VLM）。開發者只需透過安裝環境、轉換模型、執行推論三個簡單步驟，即可在無獨立顯卡的 Intel 硬體上實現高效的多模態處理，大幅降低 VLM 的本地部署門檻，非常適合邊緣運算與個人開發環境。
Visual Language Models (VLMs) combine computer vision with natural language processing, enabling complex tasks such as image captioning and visual question answering (VQA). However, VLMs typically have enormous parameter counts, and traditionally require high-end GPUs to run smoothly. To enable more developers to deploy VLMs on edge devices or personal computers without discrete graphics cards, Hugging Face has partnered with Intel to demonstrate how to efficiently run VLMs on Intel CPUs using the OpenVINO toolkit — in just three simple steps.
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