lucataco / ssd-1b-img2img

Segmind Stable Diffusion Model (SSD-1B) img2img

  • Public
  • 3.6K runs
  • L40S
  • Paper
  • License

Input

image
*file

Input image

string
Shift + Return to add a new line

Input prompt

Default: "a wolf with pink and blue fur"

string
Shift + Return to add a new line

Negative Input prompt

Default: "scary, cartoon, painting"

string

scheduler

Default: "K_EULER"

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 20

number
(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 8

number
(minimum: 0, maximum: 1)

strength/weight

Default: 0.9

integer

Random seed. Leave blank to randomize the seed

Output

output
Generated in

Run time and cost

This model costs approximately $0.0034 to run on Replicate, or 294 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 L40S GPU hardware. Predictions typically complete within 4 seconds.

Readme

About

Attempt at implementing segmind/SSD-1B for img2img

@article{kim2023architectural,
  title={On Architectural Compression of Text-to-Image Diffusion Models},
  author={Kim, Bo-Kyeong and Song, Hyoung-Kyu and Castells, Thibault and Choi, Shinkook},
  journal={arXiv preprint arXiv:2305.15798},
  year={2023},
  url={https://arxiv.org/abs/2305.15798}
}