batouresearch / dpo-sdxl-controlnet-lora

DPO-SDXL Canny controlnet with LoRA support.

  • Public
  • 641 runs
  • L40S
  • GitHub

Input

image
string
Shift + Return to add a new line

Input prompt

Default: "An astronaut riding a rainbow unicorn"

string
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Input Negative Prompt

Default: ""

file

Input image for img2img or inpaint mode

number
(minimum: 0, maximum: 1)

The bigger this number is, the more ControlNet interferes

Default: 0.5

integer
(minimum: 1, maximum: 4)

Number of images to output

Default: 1

string

scheduler

Default: "K_EULER"

integer
(minimum: 1, maximum: 500)

Number of denoising steps

Default: 50

number
(minimum: 1, maximum: 50)

Scale for classifier-free guidance

Default: 7.5

integer

Random seed. Leave blank to randomize the seed

string

Whether to use refinement steps or not

Default: "base_image_refiner"

integer

For base_image_refiner, the number of steps to refine

Default: 10

boolean

Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.

Default: true

number
(minimum: 0, maximum: 1)

LoRA additive scale. Only applicable on trained models.

Default: 0.6

string
Shift + Return to add a new line

Replicate LoRA weights to use. Leave blank to use the default weights.

Output

output
Generated in

Run time and cost

This model costs approximately $0.059 to run on Replicate, or 16 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 61 seconds. The predict time for this model varies significantly based on the inputs.

Readme

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