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Working on the improvement of the output of the stable diffusion model.
Working on the analysis of various base models, we aim to leverage stable diffusion techniques to identify models that exhibit reduced training time while maintaining stable performance.
Working on the adjustment of parameters such as lr_warmup_steps and num_class_images, we are actively working towards reducing the training time with fewer training images of the stable diffusion model.
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