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afiaka87 /pyglide:d0b38636

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
Text prompt to use. Keep it simple/literal and avoid using poetic language (unlike CLIP).
batch_size
integer
3

Min: 1

Max: 8

Batch size. Number of generations to predict
side_x
integer (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
integer (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.
upsample_stage
boolean
False
If true, uses both the base and upsample models. If false, only the (finetuned) base model is used. This is useful for testing the upsampler, which is not finetuned.
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.
upsample_temp
string (enum)
0.998

Options:

0.996, 0.997, 0.998, 0.999, 1.0

Upsample temperature. Consider lowering to ~0.997 for blurry images with fewer artifacts.
timestep_respacing
string (enum)
35

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
{'items': {'format': 'uri', 'type': 'string'},
 'title': 'Output',
 'type': 'array',
 'x-cog-array-type': 'iterator'}