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Vision Language Models : Building Vlms with Hugging Face - Andres Marafioti
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Vision Language Models

Building Vlms with Hugging Face

By: Andres Marafioti, Orr Zohar, Miquel Farre, Merve Noyan

Paperback | 14 July 2026

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Vision language models (VLMs) combine computer vision and natural language processing to create powerful systems that can interpret, generate, and respond in multimodal contexts. Vision Language Models is a hands-on guide to building real-world VLMs using the most up-to-date stack of machine learning tools from Hugging Face, Meta (PyTorch), NVIDIA (Cuda), and others, written by leading researchers and practitioners Merve Noyan, Miquel Farr©, Andr©s Marafioti, and Orr Zohar. From image captioning and document understanding to advanced zero-shot inference and retrieval-augmented generation (RAG), this book covers the full VLM application and development lifecycle. Designed for ML engineers, data scientists, and developers, this guide distills cutting-edge VLM research into practical techniques. Readers will learn how to prepare datasets, select the right architectures, fine-tune and deploy models, and apply them to real-world tasks across a range of industries. Explore core model architectures and alignment techniquesTrain and fine-tune VLMs with Hugging Face, PyTorch, and othersDeploy models for applications like image search and captioningImplement advanced inference strategies, from zero-shot to agentic systemsBuild scalable VLM systems ready for production use

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