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MOSS Image model optimization: Samplers and schedulers tested for Stable Diffusion

A user on Reddit shared their findings on optimizing image generation with the MOSS Image model, a Stable Diffusion variant. They tested various samplers and schedulers, recommending combinations like dpmpp_sde/radiance_shift for better prompt adherence. The user also noted that certain schedulers tended to generate images of Asian women. Their tests were conducted using an SFT model with an 8-step SFT lora at a strength of 0.7 and a resolution of 1536x1536, with each image taking approximately 28 seconds to generate on an NVIDIA 3090 graphics card. AI

IMPACT Provides insights into fine-tuning parameters for specific AI image generation models, potentially improving user results.

RANK_REASON User-generated guide on optimizing a specific AI model's parameters.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MOSS Image model optimization: Samplers and schedulers tested for Stable Diffusion

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1 / 100
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Tool
User-generated guide on optimizing a specific AI model's parameters.
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Full methodology in our editorial standards.

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/mikemend ·

    MOSS Image - samplers and schedulers

    <!-- SC_OFF --><div class="md"><p>I tested a few samplers and schedulers on the MOSS Image model in addition to Euler. These are worth using if you want to try out realistic images, I got pretty good results with them even at cfg 3:</p> <p><strong>samplers:</strong> heun, heunpp2…