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teddykoker.com
| | www.nicktasios.nl
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| | In the Latent Diffusion Series of blog posts, I'm going through all components needed to train a latent diffusion model to generate random digits from the MNIST dataset. In this first post, we will tr
| | comsci.blog
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| | In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture.
| | harvardnlp.github.io
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| | [AI summary] The provided code is a comprehensive implementation of the Transformer model, including data loading, model architecture, training, and visualization. It also includes functions for decoding and visualizing attention mechanisms across different layers of the model. The code is structured to support both training and inference, with examples provided for running the model and visualizing attention patterns.
| | blog.paperspace.com
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| Follow this tutorial to learn what attention in deep learning is, and why attention is so important in image classification tasks. We then follow up with a demo on implementing attention from scratch with VGG.