asiryan / 2dn-xl

2DN XL Model (Text2Img, Img2Img and Inpainting)

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

string
Shift + Return to add a new line

Input prompt

Default: "source_anime, score_9,score_8_up,score_7_up,score_6_up,score_5_up,score_4_up,(androgynous), ([1boy|1girl]), gender neutral, light purple hair, pastel colors, dark purple eyes, snow"

string
Shift + Return to add a new line

Negative Input prompt

Default: "score_6, score_5, score_4, bad quality, bad anatomy, worst quality, low quality, low resolutions, extra fingers, blur, blurry, ugly, wrongs proportions, watermark, image artifacts, lowres, jpeg artifacts, deformed, noisy image, poorly drawn face, ugly face, crossed eyes"

file

Input image for img2img or inpaint mode

file

Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.

integer

Width of output image

Default: 1024

integer

Height of output image

Default: 1024

integer
(minimum: 1, maximum: 4)

Number of images to output.

Default: 1

string

scheduler

Default: "K_EULER_ANCESTRAL"

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 40

number
(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 3.5

number
(minimum: 0, maximum: 1)

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image

Default: 0.8

integer

Random seed. Leave blank to randomize the seed

Including lora_scale and 1 more...

Output

output
Generated in

Run time and cost

This model costs approximately $0.0066 to run on Replicate, or 151 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 5 seconds.

Readme

2DN XL Model (Text2Img, Img2Img and Inpainting)