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Stable Diffusion user experiments with high-rank, high-resolution LoRA training

A user on Reddit is experimenting with training LoRAs (Low-Rank Adaptation) for Stable Diffusion using significantly larger datasets and higher resolutions than typically employed. They aim to preserve character identity by pushing parameters like rank up to 1024 and resolutions to 2048, seeking insights from others who have attempted similar high-parameter training. AI

IMPACT This user's experimentation may offer insights into pushing the boundaries of LoRA training for improved identity preservation in AI-generated images.

RANK_REASON User-level experimentation with a specific AI model's training parameters.

Read on r/StableDiffusion →

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

Stable Diffusion user experiments with high-rank, high-resolution LoRA training

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/Business-Chocolate-4 ·

    High rank / high res experiment for huge dataset

    <!-- SC_OFF --><div class="md"><p>Hi everyone. I’ve been making character loras (of myself) for about 3 years. I have used big datasets (1000-1500 pics) and so far have gotten away with great results with 96-128 rank (low learning rate of course and and batch 1 usually) and have …