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(CA) MossImage quants & SFT fix

MossImage optimizations and SFT fixes detailed for Stable Diffusion users

A Reddit post on r/StableDiffusion discusses optimizations and fixes for the MossImage model, specifically focusing on quantization and supervised fine-tuning (SFT). The author recommends using INT8 quantization for users with NVIDIA RTX20x+ or RDNA2 GPUs, and suggests GGUF quants for those with limited VRAM or slower performance. Additionally, a banding fix LoRA and render speedup LoRA are mentioned, along with an upgrade for Flux VAE. AI

IMPACT Provides technical guidance for optimizing image generation models, potentially improving performance and accessibility for users.

RANK_REASON Discussion of optimizations and fixes for an existing open-source image generation model.

Read on r/StableDiffusion →

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

MossImage optimizations and SFT fixes detailed for Stable Diffusion users

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Discussion of optimizations and fixes for an existing open-source image generation model.
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COVERAGE [1]

  1. r/StableDiffusion TIER_2 (CA) · /u/tomByrer ·

    MossImage quant & SFT fix

    <!-- SC_OFF --><div class="md"><p><a href="https://huggingface.co/Abiray/MOSS-Image-SFT-INT8-convrot">https://huggingface.co/Abiray/MOSS-Image-SFT-INT8-convrot</a></p> <p>I recommend the INT8 as a start. nVidia RTX20x+ &amp; <strong>RDNA2</strong> (RX6000)+ are good. ARM needs fa…