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afiaka87/laionide-v4:b21cbe27

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
Prompt to use.
style_prompt
string (enum)
<pixelart>

Options:

<pixelart>, <cc12m>, <pokemon>, <country211>, <openimages>, <ffhq>, <coco>, <vaporwave>, <virtualgenome>, <imagenet>

Additional style guidance to use. Handles any sequence of tokens, but works particularly well on the listed pretrained 'dataset tokens'.
batch_size
integer
1

Min: 1

Max: 8

Batch size. Number of generations to predict
side_x
string (enum)
64

Options:

32, 48, 64, 80, 96, 112, 128

Must be multiple of 8. Going above 64 is not recommended. Actual image will be 4x larger.
side_y
string (enum)
64

Options:

32, 48, 64, 80, 96, 112, 128

Must be multiple of 8. Going above 64 is not recommended. Actual image size will be 4x larger.
upsample_stage
boolean
True
If true, uses both the base and upsample models. If false, only the (finetuned) base model is used.
upsample_temp
string (enum)
0.997

Options:

0.996, 0.997, 0.998, 0.999, 1.0

Upsample temperature. Consider lowering to ~0.997 for blurry images with fewer artifacts.
guidance_scale
number
4
Classifier-free guidance scale. Higher values move further away from unconditional outputs. Lower values move closer to unconditional outputs. Negative values guide towards semantically opposite classes. 4-16 is a reasonable range.
style_guidance_scale
number
4
Same as guidance scale, but applied to glide model outputs from the style prompt instead of the prompt.
timestep_respacing
string (enum)
27

Options:

15, 17, 19, 21, 23, 25, 27, 30, 35, 40, 50, 100

Number of timesteps to use for base model PLMS sampling. Usually don't need more than 50.
sr_timestep_respacing
string (enum)
17

Options:

15, 17, 19, 21, 23, 25, 27

Number of timesteps to use for upsample model PLMS sampling. Usually don't need more than 20.
seed
integer
0
Seed for reproducibility

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}