Digital Human Experiment

 



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Big Data - Regression & Classification algorithms

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Automatic 1111 Stable Diffusion (September 29th, 2023)

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Automatic 1111 Stable Diffusion September 29th, 2023 I installed automatic 1111 stable diffusion. I never experimented with the sampling methods until now. I didn’t expect the image to change completely when changing the sampling method, even though I kept the same seed. Some sampling methods produce similar or identical results such as PLMS, DPM++ 2M, LMS Karras, and DPM2 Karras. I experimented with different CFG scales too and actually referred to the model I used called absolute reality . The details for that model said to use cfg 4.5-10 but I actually liked the result I got from a cfg scale of 3. I put the cfg scale at the highest (30) and the image came out bad, the shapes weren’t well defined and it didn’t have much detail.  I started with the default sampling steps at 20 and then tried the maximum. The maximum sampling steps came out nice so I kept my sampling step at 150.  Something that I learned from your last lecture is to always check the notes from any model I use...
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