bluematter
/
cog-test
- Public
- 0 runs
Run bluematter/cog-test with an API
Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.
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
|
abstract beauty, centered, looking at the camera, approaching perfection, dynamic, moonlight, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by Carne Griffiths and Wadim Kashin
|
Input prompt
|
| negative_prompt |
string
|
(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)
|
Negative Input prompt
|
| image |
string
|
Input image for img2img or inpaint mode
|
|
| mask |
string
|
Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
|
|
| width |
integer
|
1024
|
Width of output image
|
| height |
integer
|
1024
|
Height of output image
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| scheduler |
string
(enum)
|
K_EULER_ANCESTRAL
Options: DDIM, DPMSolverMultistep, HeunDiscrete, KarrasDPM, K_EULER_ANCESTRAL, K_EULER, PNDM |
scheduler
|
| num_inference_steps |
integer
|
40
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| strength |
number
|
0.8
Max: 1 |
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| lora_scale |
number
|
0.6
Max: 1 |
LoRA additive scale. Only applicable on trained models.
|
| lora_weights |
string
|
Replicate LoRA weights to use. Leave blank to use the default weights.
|
{
"type": "object",
"title": "Input",
"properties": {
"mask": {
"type": "string",
"title": "Mask",
"format": "uri",
"x-order": 3,
"description": "Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted."
},
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 11,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 2,
"description": "Input image for img2img or inpaint mode"
},
"width": {
"type": "integer",
"title": "Width",
"default": 1024,
"x-order": 4,
"description": "Width of output image"
},
"height": {
"type": "integer",
"title": "Height",
"default": 1024,
"x-order": 5,
"description": "Height of output image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "abstract beauty, centered, looking at the camera, approaching perfection, dynamic, moonlight, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by Carne Griffiths and Wadim Kashin",
"x-order": 0,
"description": "Input prompt"
},
"strength": {
"type": "number",
"title": "Strength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 10,
"description": "Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image"
},
"scheduler": {
"enum": [
"DDIM",
"DPMSolverMultistep",
"HeunDiscrete",
"KarrasDPM",
"K_EULER_ANCESTRAL",
"K_EULER",
"PNDM"
],
"type": "string",
"title": "scheduler",
"description": "scheduler",
"default": "K_EULER_ANCESTRAL",
"x-order": 7
},
"lora_scale": {
"type": "number",
"title": "Lora Scale",
"default": 0.6,
"maximum": 1,
"minimum": 0,
"x-order": 12,
"description": "LoRA additive scale. Only applicable on trained models."
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 6,
"description": "Number of images to output."
},
"lora_weights": {
"type": "string",
"title": "Lora Weights",
"x-order": 13,
"description": "Replicate LoRA weights to use. Leave blank to use the default weights."
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7,
"maximum": 50,
"minimum": 1,
"x-order": 9,
"description": "Scale for classifier-free guidance"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)",
"x-order": 1,
"description": "Negative Input prompt"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 40,
"maximum": 500,
"minimum": 1,
"x-order": 8,
"description": "Number of denoising steps"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}