xinli2008/diffusion_transformer_from_scratch
从0到1手写基于mnist手写数字数据集的diffusion transformer模型复现
This project helps machine learning researchers and students understand and implement a Diffusion Transformer model from scratch. It takes conceptual knowledge of diffusion models and transformer architectures and provides a concrete example using the MNIST dataset. The output is a working, reimplemented model that generates handwritten digits.
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Use this if you are a machine learning student or researcher looking to deepen your understanding of Diffusion Transformers by building one from the ground up, specifically for image generation on a well-known dataset.
Not ideal if you are looking for a ready-to-use, high-performance diffusion model for complex, real-world image generation tasks or advanced research applications beyond basic educational purposes.
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Python
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Last pushed
Dec 02, 2024
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