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adirik /t2i-adapter-sdxl-depth-midas:8a89b0ab
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 |
|---|---|---|---|
| image |
string
|
Input image
|
|
| prompt |
string
|
A photo of a room, 4k photo, highly detailed
|
Input prompt
|
| negative_prompt |
string
|
anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured
|
Specify things to not see in the output
|
| num_inference_steps |
integer
|
30
Max: 100 |
Number of diffusion steps
|
| adapter_conditioning_scale |
number
|
1
Max: 5 |
Conditioning scale
|
| adapter_conditioning_factor |
number
|
1
Max: 1 |
Factor to scale image by
|
| guidance_scale |
number
|
7.5
Max: 10 |
Guidance scale to match the prompt
|
| num_samples |
integer
|
1
Min: 1 Max: 4 |
Number of outputs to generate
|
| scheduler |
string
(enum)
|
K_EULER_ANCESTRAL
Options: DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM, LMSDiscrete |
Which scheduler to use
|
| random_seed |
integer
|
Random seed for reproducibility, leave blank to randomize output
|
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'}