Introduction
Transformers for computer vision
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What you should know
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1. Transformer Architecture
History of transformers
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Comparing Vision Transformers to BERT
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2. Datasets and Preprocessing
Getting set up
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Getting the data
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Using datasets
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Using a pretrained model without fine-tuning
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Defining a model
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Preprocessing images
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A transformed image
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Getting images in the correct format
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3. Model Training
Training arguments
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Model training
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Inference in notebook
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Inference on phone using Gradio
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Gradio and Hugging Face Spaces
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Conclusion
Learn more about transformers and large language models
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Glossary_Advanced_AI_Transformers_Computer_Vision.zip
(40 KB)