Vision Language Models

Building VLMs with Hugging Face

By: Merve Noyan, Andrés Marafioti, Orr Zohar, Miquel Farré

Write A Review

eText | 8 June 2026 | Edition Number 1

At a Glance

Format
ePUB

eText

$85.79

or 4 interest-free payments of $21.45 with

Instant online reading in your Booktopia eTextbook Library *

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

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.