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georgedavila /cog-storydiffusion-comics:761766d0
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 |
|---|---|---|---|
| input_image |
string
|
None
|
|
| style |
string
|
Photographic
|
Style template: '(No style)', 'Japanese Anime', 'Cinematic', 'Disney Character', 'Photographic', 'Comic book', 'Line art'
|
| style_strength_ratio |
integer
|
20
|
Style strength of Ref Image (%)
|
| model_type |
string
(enum)
|
Using Ref Images
Options: Only Using Textual Description, Using Ref Images |
Control type of the Character
|
| general_prompt |
string
|
a man img, wearing a tuxedo
|
Textual Description for Character
|
| negative_prompt |
string
|
bad anatomy, bad hands, missing fingers, extra fingers, three hands, three legs, bad arms, missing legs, missing arms, poorly drawn face, bad face, fused face, cloned face, three crus, fused feet, fused thigh, extra crus, ugly fingers, horn, cartoon, cg, 3d, unreal, animate, amputation, disconnected limbs
|
Negative Prompt
|
| prompt_array |
string
|
wake up in the bed
have breakfast
is on the road, go to company
work in the company
Take a walk next to the company at noon
lying in bed at night
|
Comic Description (each line corresponds to a frame).
|
| Ip_Adapter_Strength |
number
|
0.7
|
Ip Adapter Strength
|
| sa32_ |
number
|
0.5
|
The degree of Paired Attention at 32 x 32 self-attention layers
|
| sa64_ |
number
|
0.5
|
The degree of Paired Attention at 64 x 64 self-attention layers
|
| id_length_ |
integer
|
3
|
Number of id images in total images
|
| seed_ |
integer
|
1
|
Seed
|
| num_steps |
integer
|
50
|
Number of sample steps
|
| G_height |
integer
|
768
|
Height
|
| G_width |
integer
|
768
|
Width
|
| comic_type |
string
(enum)
|
Classic Comic Style
Options: Classic Comic Style, No typesetting |
Typesetting Style
|
| guidance_scale |
integer
|
5
|
Guidance scale
|
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'}