After training 50+ LoRA Models here is what I learned (TIPS)

• ddetailer

  12 335 3.8 Python

One way to avoid the inpainting issue is to use Ddetailer or Adetailer to auto-inpaint detected faces. I use the latter as I couldn't get ddetailer to work, but the fundamental feature is the same. It does a face-detection and inpainting pass after the initial generation (and hires fix), which means your first output already has the face fixed somewhat. And then you can go in to correct smaller details.

• adetailer

  43 3,682 9.5 Python

  Auto detecting, masking and inpainting with detection model.

One way to avoid the inpainting issue is to use Ddetailer or Adetailer to auto-inpaint detected faces. I use the latter as I couldn't get ddetailer to work, but the fundamental feature is the same. It does a face-detection and inpainting pass after the initial generation (and hires fix), which means your first output already has the face fixed somewhat. And then you can go in to correct smaller details.

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• sd_dreambooth_extension

  115 1,818 9.0 Python

After months of wrangling with Dreambooth, I finally mastered how to use it. The training rate is the key. I found a spreadsheet on the Dreambooth webui extension github discussion forum. I don't know if most people are aware of it. For me, it has been extremely reliable. In fact, I think the formulas in it should be built into Dreambooth trainers.

• kohya_ss

  132 8,248 9.8 Python

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