During his talk, Alexander discussed how the application of low-rank adaptation techniques in the context of fine-tuning stabilized diffusion processes, enhancing their efficiency and accuracy in various computational tasks. In the talk, he shared insights about existing fine-tuning techniques for Stable Diffusion models, including hypernetworks and low-rank adaptation techniques, highlighting their advantages and disadvantages and illustrating how they could be applied to all sorts of models, not limited to image generation. The attendees gained valuable insights into incorporating this approach into their downstream tasks.
This speech by Alexander Kovalchuk was held on November 23rd at Data Science Conference Europe 2023 in Belgrade.
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Негізгі бет Finetuning Stable Diffusion with low-rank adaptation techniques | A. Kovalchuk | DSC Europe 23
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