Stable Diffusion Webgpu

Image Generation

Stable Diffusion Webgpu

Run Stable Diffusion in Your Browser with WebGPU Acceleration

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About Stable Diffusion Webgpu

Stable Diffusion WebGPU is a cutting-edge tool that revolutionizes the way users interact with image generation on their web browsers. Taking full advantage of the latest Chrome technologies, this tool supports high-performance, AI-driven image generation directly within the web environment, making the process incredibly efficient and user-friendly. By enabling WebAssembly and JavaScript Promise Integration within Chrome Canary, users can experience seamless and rapid image processing, transforming their creative ideas into visual art with minimal delay and maximum precision. The user-centric design of Stable Diffusion WebGPU allows for easy model download and straightforward usage. With models stored directly in the browser cache, accessibility and swift model operations are at your fingertips. Users can load models, run them, and be ready to delve into creative processes almost instantaneously. The interface also provides editable settings post-download, ensuring that every image generation task is tailored precisely to the user’s requirements. Moreover, the platform addresses common issues and offers solutions, enhancing user experience and reducing potential frustrations. The FAQs section provides clear instructions for resolving protobuf parsing errors and memory limitations. The technology behind Stable Diffusion WebGPU, including the porting of StableDiffusionPipeline from Python to JS, and support for extensive memory use through patched onnxruntime and WebAssembly compiler toolchains, sets a new standard for browser-based AI applications. This tool not only brings high-quality image generation to your browser but also places powerful, customizable features within easy reach, making it an invaluable resource for digital creatives.

Key Features

  • GPU acceleration in-browser
  • Customizable image generation settings
  • Direct model download to browser cache
  • Support for experimental WebAssembly flags
  • Ability to run VAE after each inference step
  • Error troubleshooting via FAQ
  • Ported StableDiffusionPipeline from Python to JavaScript
  • Large memory allocation support with onnxruntime and emscripten+binaryen
  • FP16 support with recent Chrome versions
  • Seamless integration with web technologies

Tags

WebGPUStable Diffusionimage generationbrowserGPU accelerationsettings customizationtroubleshootingdownloadcacheChromeexperimental flagspromptguidance scaleinference steps

FAQs

What if I get protobuf parsing failed error?
Open DevTools, go to Application -> Storage, and press 'Clear site data'.
What if I get sbox_fatal_memory_exceeded?
You don't have enough RAM to run SD. Try reloading the tab or browser.
How did you make it possible?
StableDiffusionPipeline was ported from Python to JavaScript, and onnxruntime and emscripten+binaryen were patched to support more than 4GB of memory.
Which version of Chrome is required?
You need Chrome Canary 119 or newer. Chrome Canary 121 or higher is required for FP16 support.
Where is the model stored after download?
The model is stored in your browser cache.
What are the customizable settings for image generation?
Settings include prompt, negative prompt, number of inference steps, guidance scale, seed, and running VAE after each step.
What are the options available after downloading the model?
Options available are Load model, Run, and Ready.
Do specific flags need to be enabled in Chrome?
Yes, you need 'Experimental WebAssembly' and 'Experimental WebAssembly JavaScript Promise Integration (JSPI)' flags enabled.
What is the PNDM Scheduler?
It influences the number of steps in generating the image.
What if I encounter other issues?
Consult the FAQ section for common issues or seek support from the service provider.