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Vision Transformer (ViT) Implementation In TensorFlow
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In this video, we will implement the Vision Transformer (ViT) from scratch in the TensorFlow framework using the Keras API.
Vision transformer (ViT) is a transformer-based architecture used in the field of computer vision, it is directly inspired by the use of Transformers in NLP tasks.
Timeline:
00:00 - Introduction
00:25 - What is Vision Transformer?
02:47 - Input Image to Patch Processing used in Vision Transformer
06:05 - Transformer Encoder
07:14 - Variants of Vision Transformer: ViT-Base, ViT-Large, ViT-Huge
07:44 - Importing all required libraries
08:43 - Begining with the __main__ and writing ViT variants configuration
09:32 - Vision Transformer Implementation
35:00 - Ending - SUBSCRIBE
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Follow Me:
Vision transformer (ViT) is a transformer-based architecture used in the field of computer vision, it is directly inspired by the use of Transformers in NLP tasks.
Timeline:
00:00 - Introduction
00:25 - What is Vision Transformer?
02:47 - Input Image to Patch Processing used in Vision Transformer
06:05 - Transformer Encoder
07:14 - Variants of Vision Transformer: ViT-Base, ViT-Large, ViT-Huge
07:44 - Importing all required libraries
08:43 - Begining with the __main__ and writing ViT variants configuration
09:32 - Vision Transformer Implementation
35:00 - Ending - SUBSCRIBE
Support:
Follow Me:
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