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pwntus /sdxl-gta-v:b61a50b0

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
An astronaut riding a rainbow unicorn
Input prompt
negative_prompt
string
Input Negative Prompt
image
string
Input image for img2img or inpaint mode
mask
string
Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
width
integer
1024
Width of output image
height
integer
1024
Height of output image
num_outputs
integer
1

Min: 1

Max: 4

Number of images to output.
scheduler
string (enum)
K_EULER

Options:

DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM

scheduler
num_inference_steps
integer
50

Min: 1

Max: 500

Number of denoising steps
guidance_scale
number
7.5

Min: 1

Max: 50

Scale for classifier-free guidance
prompt_strength
number
0.8

Max: 1

Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
seed
integer
Random seed. Leave blank to randomize the seed
refine
string (enum)
no_refiner

Options:

no_refiner, expert_ensemble_refiner, base_image_refiner

Which refine style to use
high_noise_frac
number
0.8

Max: 1

For expert_ensemble_refiner, the fraction of noise to use
refine_steps
integer
For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
apply_watermark
boolean
True
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.
lora_scale
number
0.6

Max: 1

LoRA additive scale. Only applicable on trained models.

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'}