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You're reading from  Transformers for Natural Language Processing and Computer Vision - Third Edition

Product typeBook
Published inFeb 2024
Reading LevelN/a
PublisherPackt
ISBN-139781805128724
Edition3rd Edition
Languages
Python
Tools
PyTorch
Concepts
Deep Learning
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Author (1)
Denis Rothman
Denis Rothman
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Denis Rothman

Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
Read more about Denis Rothman

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DALL-E 2 and DALL-E 3

DALL-E, as with CLIP, is a multimodal model. CLIP processes text-image pairs. DALL-E processes the text and image tokens differently. DALL-E 1 has an input of a single stream of text and image of 1,280 tokens. 256 tokens are for the text, and 1,024 tokens are used for the image.

DALL-E was named after Salvador Dali and Pixar’s WALL-E. The usage of DALL-E is to enter a text prompt and produce an image. However, DALL-E must first learn how to generate images with text.

This transformer generates images from text descriptions using a dataset of text-image pairs.

We will go through the basic architecture of DALL-E to see how the model works.

The basic architecture of DALL-E

Unlike CLIP, DALL-E concatenates up to 256 BPE-encoded text tokens with 32×32 = 1,024 image tokens, as shown in Figure 16.11:

A screenshot of a video game Description automatically generated with medium confidence

Figure 16.11: DALL-E concatenates text and image input

Figure 16.11 shows that, this time, our cat image is concatenated with...

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Transformers for Natural Language Processing and Computer Vision - Third Edition
Published in: Feb 2024Publisher: PacktISBN-13: 9781805128724
© 2024 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Denis Rothman

Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
Read more about Denis Rothman

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