fofr/qwen-black-goya-training
Run fofr/qwen-black-goya-training 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
|
A beautiful sunset over mountains
|
Prompt for generated image
|
| enhance_prompt |
boolean
|
False
|
Enhance the prompt with positive magic
|
| negative_prompt |
string
|
|
Negative prompt for generated image
|
| aspect_ratio |
None
|
16:9
|
Aspect ratio
|
| image_size |
None
|
optimize_for_quality
|
Image size preset
|
| width |
integer
|
512
Min: 256 Max: 1024 |
Width (overrides aspect_ratio/image_size)
|
| height |
integer
|
512
Min: 256 Max: 1024 |
Height (overrides aspect_ratio/image_size)
|
| go_fast |
boolean
|
False
|
Run faster with minor optimizations
|
| num_inference_steps |
integer
|
50
Min: 1 Max: 50 |
Number of denoising steps
|
| guidance |
number
|
4
Max: 10 |
Guidance scale
|
| seed |
integer
|
Random seed (leave blank for random)
|
|
| output_format |
None
|
webp
|
Output format
|
| output_quality |
integer
|
80
Max: 100 |
Quality for jpg/webp
|
| replicate_weights |
string
|
LoRA weights (.safetensors or .zip)
|
|
| lora_scale |
number
|
1
Max: 3 |
LoRA strength
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 10,
"nullable": true,
"description": "Random seed (leave blank for random)"
},
"width": {
"type": "integer",
"title": "Width",
"default": 512,
"maximum": 1024,
"minimum": 256,
"x-order": 5,
"description": "Width (overrides aspect_ratio/image_size)"
},
"height": {
"type": "integer",
"title": "Height",
"default": 512,
"maximum": 1024,
"minimum": 256,
"x-order": 6,
"description": "Height (overrides aspect_ratio/image_size)"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "A beautiful sunset over mountains",
"x-order": 0,
"description": "Prompt for generated image"
},
"go_fast": {
"type": "boolean",
"title": "Go Fast",
"default": false,
"x-order": 7,
"description": "Run faster with minor optimizations"
},
"guidance": {
"type": "number",
"title": "Guidance",
"default": 4,
"maximum": 10,
"minimum": 0,
"x-order": 9,
"description": "Guidance scale"
},
"image_size": {
"enum": [
"optimize_for_quality",
"optimize_for_speed"
],
"type": "string",
"title": "image_size",
"description": "Image size preset",
"default": "optimize_for_quality",
"x-order": 4
},
"lora_scale": {
"type": "number",
"title": "Lora Scale",
"default": 1,
"maximum": 3,
"minimum": 0,
"x-order": 14,
"description": "LoRA strength"
},
"aspect_ratio": {
"enum": [
"1:1",
"16:9",
"9:16",
"4:3",
"3:4"
],
"type": "string",
"title": "aspect_ratio",
"description": "Aspect ratio",
"default": "16:9",
"x-order": 3
},
"output_format": {
"enum": [
"webp",
"jpg",
"png"
],
"type": "string",
"title": "output_format",
"description": "Output format",
"default": "webp",
"x-order": 11
},
"enhance_prompt": {
"type": "boolean",
"title": "Enhance Prompt",
"default": false,
"x-order": 1,
"description": "Enhance the prompt with positive magic"
},
"output_quality": {
"type": "integer",
"title": "Output Quality",
"default": 80,
"maximum": 100,
"minimum": 0,
"x-order": 12,
"description": "Quality for jpg/webp"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "",
"x-order": 2,
"description": "Negative prompt for generated image"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 50,
"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.
{
"type": "string",
"title": "Output",
"format": "uri"
}