LoRA Extraction Effect Enhancement Program
Feature extraction can be optimized by the following method:
- Data preprocessing::
- Ensure uniform image resolution (512 x 512 recommended)
- Detailed .txt description files for each image, labeling key features using [trigger]
- parameter tuning::
- modifications
linearcap (a poem)linear_alphaValues (recommended in the range 128-256) - rise
network_dimDimension (≤64 recommended for 24GB video memory devices)
- modifications
- Auxiliary tool applications::
- Using the built-in
LoCON提取工具Analyzing Feature Distribution - pass (a bill or inspection etc)
Gradio UIReal-time preview of extraction results
- Using the built-in
Typical problems are dealt with:
In case of feature obfuscation, you can add a configuration file to thedropout: 0.1-0.3Enhanced generalization capabilities
This answer comes from the articleAI Toolkit by Ostris: Stable Diffusion with FLUX.1 Model Training ToolkitThe
May not be reproduced without permission:AI productivity tools " How to optimize the feature extraction effect of LoRA model?
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