anotherjesse
/
openjourney-v4-lora
- Public
- 25 runs
Run anotherjesse/openjourney-v4-lora 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 photo of <1> riding a horse on mars
|
Input prompt. Use <1>, <2>, <3>, etc., to specify LoRA concepts
|
negative_prompt |
string
|
|
Specify things to not see in the output
|
width |
integer
(enum)
|
512
Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024 |
Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
|
height |
integer
(enum)
|
512
Options: 128, 256, 384, 448, 512, 576, 640, 704, 768, 832, 896, 960, 1024 |
Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits
|
num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
num_inference_steps |
integer
|
50
Min: 1 Max: 500 |
Number of denoising steps
|
guidance_scale |
number
|
7.5
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
image |
string
|
(Img2Img) Inital image to generate variations of. If this is not none, Img2Img will be invoked.
|
|
prompt_strength |
number
|
0.8
|
(Img2Img) Prompt strength when providing the image. 1.0 corresponds to full destruction of information in init image
|
scheduler |
string
(enum)
|
DPMSolverMultistep
Options: DDIM, K_EULER, DPMSolverMultistep, K_EULER_ANCESTRAL, PNDM, KLMS |
Choose a scheduler.
|
lora_urls |
string
|
|
List of urls for safetensors of lora models, seperated with | .
|
lora_scales |
string
|
0.5
|
List of scales for safetensors of lora models, seperated with |
|
seed |
integer
|
Random seed. Leave blank to randomize the seed
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 12,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 7,
"description": "(Img2Img) Inital image to generate variations of. If this is not none, Img2Img will be invoked."
},
"width": {
"enum": [
128,
256,
384,
448,
512,
576,
640,
704,
768,
832,
896,
960,
1024
],
"type": "integer",
"title": "width",
"description": "Width of output image. Maximum size is 1024x768 or 768x1024 because of memory limits",
"default": 512,
"x-order": 2
},
"height": {
"enum": [
128,
256,
384,
448,
512,
576,
640,
704,
768,
832,
896,
960,
1024
],
"type": "integer",
"title": "height",
"description": "Height of output image. Maximum size is 1024x768 or 768x1024 because of memory limits",
"default": 512,
"x-order": 3
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "a photo of <1> riding a horse on mars",
"x-order": 0,
"description": "Input prompt. Use <1>, <2>, <3>, etc., to specify LoRA concepts"
},
"lora_urls": {
"type": "string",
"title": "Lora Urls",
"default": "",
"x-order": 10,
"description": "List of urls for safetensors of lora models, seperated with | ."
},
"scheduler": {
"enum": [
"DDIM",
"K_EULER",
"DPMSolverMultistep",
"K_EULER_ANCESTRAL",
"PNDM",
"KLMS"
],
"type": "string",
"title": "scheduler",
"description": "Choose a scheduler.",
"default": "DPMSolverMultistep",
"x-order": 9
},
"lora_scales": {
"type": "string",
"title": "Lora Scales",
"default": "0.5",
"x-order": 11,
"description": "List of scales for safetensors of lora models, seperated with | "
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 4,
"description": "Number of images to output."
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7.5,
"maximum": 20,
"minimum": 1,
"x-order": 6,
"description": "Scale for classifier-free guidance"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "",
"x-order": 1,
"description": "Specify things to not see in the output"
},
"prompt_strength": {
"type": "number",
"title": "Prompt Strength",
"default": 0.8,
"x-order": 8,
"description": "(Img2Img) Prompt strength when providing the image. 1.0 corresponds to full destruction of information in init image"
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 500,
"minimum": 1,
"x-order": 5,
"description": "Number of denoising steps"
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Output"
}