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georgedavila /ay-chihuahua-sdxl-lora:5e8fddcd

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
myprompt
string
A photo
Input prompt
promptAddendum
string
in the style of TOK
Extra terms to add to end of prompt (TOK is the style-oriented term for this LoRA)
negative_prompt
string
cartoon, 3d, ((disfigured)), ((bad art)), ((deformed)),((extra limbs)),((close up)),((b&w)), wierd colors, blurry, (((duplicate))), ((morbid)), ((mutilated)), [out of frame], extra fingers, mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), out of frame, ugly, extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck))), Photoshop, video game, ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, mutation, mutated, extra limbs, extra legs, extra arms, disfigured, deformed, cross-eye, body out of frame, blurry, bad art, bad anatomy, 3d render
Negative Prompt
outWidth
integer
1024

Min: 128

Max: 4096

width of output
outHeight
integer
1024

Min: 128

Max: 4096

height of output
guidanceScale
number
7.5

Max: 50

Guidance scale (influence of input text on generation)
num_outputs
integer
1

Min: 1

Max: 4

Number of images to output.
num_inference_steps
integer
50

Min: 1

Max: 500

Number of denoising steps
seed
integer
Random seed. Leave blank to randomize the seed
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
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'}