Stable-Diffusion: Optimized for Mobile Deployment
State-of-the-art generative AI model used to generate detailed images conditioned on text descriptions
Generates high resolution images from text prompts using a latent diffusion model. This model uses CLIP ViT-L/14 as text encoder, U-Net based latent denoising, and VAE based decoder to generate the final image.
This model is an implementation of Stable-Diffusion found here. This repository provides scripts to run Stable-Diffusion on Qualcomm® devices. More details on model performance across various devices, can be found here.
—Model Details—
-Model Type: Image generation
-Model Stats:
**Input: Text prompt to generate image
**QNN-SDK: 2.19
**Text Encoder Number of parameters: 340M
**UNet Number of parameters: 865M
**VAE Decoder Number of parameters: 83M
**Model size: 1GB
State-of-the-art generative AI model used to generate detailed images conditioned on text descriptions
Generates high resolution images from text prompts using a latent diffusion model. This model uses CLIP ViT-L/14 as text encoder, U-Net based latent denoising, and VAE based decoder to generate the final image.
This model is an implementation of Stable-Diffusion found here. This repository provides scripts to run Stable-Diffusion on Qualcomm® devices. More details on model performance across various devices, can be found here.
—Model Details—
-Model Type: Image generation
-Model Stats:
**Input: Text prompt to generate image
**QNN-SDK: 2.19
**Text Encoder Number of parameters: 340M
**UNet Number of parameters: 865M
**VAE Decoder Number of parameters: 83M
**Model size: 1GB