stable-diffusion-aws-extension/docs/en/user-guide/training-guide.md

Training Guide

The training is based on Kohya-SS. Kohya-SS is a Python library for finetuning stable diffusion model which is friendly for consumer-grade GPU and compatible with the Stable Diffusion WebUI. The solution can do LoRA training both on SDXL and SD 1.5.

Training User Guide

Prepare Foundation Model

Upload your local SD model to S3 bucket by following commands

# Configure credentials
aws configure
# Copy local SD model to S3 bucket
aws s3 cp *safetensors s3://<bucket_path>/<model_path>

Prepare Dataset

Execute AWS CLI command to copy the dataset to S3 bucket

aws s3 sync local_folder_name s3://<bucket_name>/<folder_name>

The folder name should be started with a number and underline, eg. 100_demo. Each image should be paired with a txt file with the same name, eg. demo1.png, demo1.txt, the demo1.txt contains the captions of demo1.png.

Invoke Training API

Refer to API document to invoke training API.