sayakpaul/xla-benchmark-sd

Provides code to serialize the different models involved in Stable Diffusion as SavedModels and to compile them with XLA.

26
/ 100
Experimental

This project helps machine learning engineers and researchers accelerate the inference speed of Stable Diffusion models. It takes the individual components of a KerasCV Stable Diffusion model, processes them into optimized SavedModels, and then compiles these with XLA to output significantly faster image generation. This allows for quicker experimentation and deployment of generative AI applications.

No commits in the last 6 months.

Use this if you are a machine learning engineer working with Stable Diffusion in TensorFlow and need to optimize the speed of image generation for research or production.

Not ideal if you are looking for a high-level API for Stable Diffusion without needing to delve into model compilation and optimization.

Machine Learning Inference Generative AI Model Optimization Deep Learning Deployment Image Generation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 14 / 25

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Stars

7

Forks

3

Language

Python

License

Last pushed

Feb 27, 2023

Commits (30d)

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