tstramer/material-diffusion

Stable diffusion fork for generating tileable outputs using v1.5 model

  • Public
  • 2M runs

Run material-diffusion with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field Type Default value Description
prompt
string
Input prompt
width
integer (enum)
512

Options:

128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
height
integer (enum)
512

Options:

128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
init_image
string
Inital image to generate variations of. Will be resized to the specified width and height
mask
string
Black and white image to use as mask for inpainting over init_image. Black pixels are inpainted and white pixels are preserved. Tends to work better with prompt strength of 0.5-0.7. Consider using https://replicate.com/andreasjansson/stable-diffusion-inpainting instead.
prompt_strength
number
0.8
Prompt strength when using init image. 1.0 corresponds to full destruction of information in init image
num_outputs
integer
1

Min: 1

Max: 10

Number of images to output. If the NSFW filter is triggered, you may get fewer outputs than this.
num_inference_steps
integer
50

Min: 1

Max: 500

Number of denoising steps
guidance_scale
number
7.5

Min: 1

Max: 20

Scale for classifier-free guidance
scheduler
string (enum)
K-LMS

Options:

DDIM, K-LMS, PNDM

Choose a scheduler. If you use an init image, PNDM will be used
seed
integer
Random seed. Leave blank to randomize the seed

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'items': {'format': 'uri', 'type': 'string'},
 'title': 'Output',
 'type': 'array'}
Example API response
View prediction
['https://replicate.delivery/pbxt/XcklpSF1o7Z1I91xQQQHFvJfltWEa3HuQpoeVVTvN7GVJhffA/out-0.png']