Training a lora (stable diffusion) [part 1]

Step by step Lora Training

Training a model is very demanding, and the result is a minimum 2GB file ; while a Lora (Low-Rank Adaptation) will be less than 150MB.

Where to start?

I would recommend this google colab link

Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb 

Step 1:

Requirements: The preparation of a set of images, and texts (dataset)

Another requirements is a google account (to use the colab link and google drive)

Each image and text's name must match - the size of the images should be 512x512 pixels 

It is convenient to use https://www.birme.net/ to resize the dataset.

For the text, best is to give a little description on each file, or to use the img2txt feature and get the terms directly from the AI.

 Only 5 images (and texts) are going to suffice, but 15 or more will make the model more reliable.

Once the dataset is complete, put these files into a folder with the number of repeats (5 or 10) and the concept (something like exp, or person, or Bcloth, etc ...)

Once ready add the datasets into the google drive

Step 2: 

Open the colab trainer

Go to github.com/linaqruf/kohya-trainer

and pick Kohya Lora Dreambooth

To be continued ...