Enhance image generation by refining Stable Diffusion XL using Amazon SageMaker | Amazon Web Services

Enhance image generation by refining Stable Diffusion XL using Amazon SageMaker | Amazon Web Services



Stable Diffusion XL by Stability AI is a text-to-image deep learning model allowing for professional image generation. Managed versions are available on Amazon SageMaker JumpStart and Amazon Bedrock, supporting diverse use cases like game character design and image upscaling. The base model aids in creative processes with generic subjects, while custom datasets fine-tune images for unique subjects using Amazon SageMaker. A step-by-step guide is provided to create a custom Stable Diffusion XL model using SageMaker for unique image generation. This automated solution simplifies the process by providing necessary code and configurations for generating distinct images promptly.

The solution consists of three logical parts, involving creating a Docker container image, training the model using LoRA fine-tuning method, and generating unique images. These steps leverage various AWS services like SageMaker, Kohya SS, CodeCommit, EventBridge, Amazon ECR, and CodeBuild. The LoRA fine-tuning method adds parameters temporarily to the base model, reducing compute requirements, storage size, and training time, making the process cost-effective at scale.

Once the model is trained, it can be used to generate custom images. SageMaker supports hosting services with custom inference containers for configuring inference endpoints. An alternative method using the Automatic1111 Stable Diffusion web UI on Amazon EC2 is demonstrated for running inference. Install the UI, download the fine-tuned model, and experiment with prompts to generate unique images.

The provided solution allows for effective training of custom LoRA models with Stable Diffusion XL 1.0, resulting in the creation of creative and unique images. The process is fully automated through a CloudFormation template, enabling rapid deployment. After successfully generating custom models, cleanup steps are provided to avoid unnecessary charges. Overall, this solution offers a streamlined approach to fine-tuning models, creating distinctive images based on custom subjects.

Article Source
https://aws.amazon.com/blogs/machine-learning/generate-unique-images-by-fine-tuning-stable-diffusion-xl-with-amazon-sagemaker/