abdullahmakhdoom / diffusers-txtnimg2img

A diffusion model that changes an input image according to provided prompt

  • Public
  • 65 runs
  • A100 (80GB)
  • GitHub
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Input

image
string
Shift + Return to add a new line

Input prompt

Default: "A fantasy landscape, trending on artstation"

string
Shift + Return to add a new line

The prompt NOT to guide the image generation. Ignored when not using guidance

*file

Inital image to generate variations of.

integer

Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

integer

Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits

Default: 512

number

Prompt strength when providing the image. 1.0 corresponds to full destruction of information in init image

Default: 0.8

integer
(minimum: 1, maximum: 8)

Number of images to output. Higher number of outputs may OOM.

Default: 1

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 25

number
(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

string

Choose a scheduler.

Default: "DPMSolverMultistep"

integer

Random seed. Leave blank to randomize the seed

Output

output
Generated in

Run time and cost

This model costs approximately $0.32 to run on Replicate, or 3 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia A100 (80GB) GPU hardware. Predictions typically complete within 4 minutes. The predict time for this model varies significantly based on the inputs.

Readme

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