zenaivn/lora-flux | API reference

Public

86 runs

Run zenaivn/lora-flux 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
lora_replicate_link	string		(Optional) Enter your lora replicate link for inference. In case you don't have your own, here is a test link: https://replicate.delivery/pbxt/mu6jfnIIdQWIMKpBXRX3AkRltbjmwEX7kERNInQptcSM3VIJA/output.zip
prompt	string	a professional photo portrait of ohwx woman	Input prompt
width	None	512	Width of output image.
height	None	640	Height of output image.s
num_outputs	integer	1 Min: 1 Max: 20	Number of images to output.
num_inference_steps	integer	30 Min: 1 Max: 500	Number of denoising steps
guidance_scale	number	3.5 Min: 1 Max: 20	Scale for classifier-free guidance
upscale_2x	boolean	False	Choose if you want to upscale the image using RealESRGAN 2x
upscale_4x	boolean	False	Choose if you want to upscale the image using RealESRGAN 4x
seed	integer	1337	Your seed for training script.

{
  "type": "object",
  "title": "Input",
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "default": 1337,
      "x-order": 9,
      "description": "Your seed for training script."
    },
    "width": {
      "enum": [
        128,
        256,
        384,
        448,
        512,
        576,
        640,
        704,
        768,
        832,
        896,
        960,
        1024,
        1280
      ],
      "type": "integer",
      "title": "width",
      "description": "Width of output image.",
      "default": 512,
      "x-order": 2
    },
    "height": {
      "enum": [
        128,
        256,
        384,
        448,
        512,
        576,
        640,
        704,
        768,
        832,
        896,
        960,
        1024,
        1280
      ],
      "type": "integer",
      "title": "height",
      "description": "Height of output image.s",
      "default": 640,
      "x-order": 3
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "default": "a professional photo portrait of ohwx woman",
      "x-order": 1,
      "description": "Input prompt"
    },
    "upscale_2x": {
      "type": "boolean",
      "title": "Upscale 2X",
      "default": false,
      "x-order": 7,
      "description": "Choose if you want to upscale the image using RealESRGAN 2x"
    },
    "upscale_4x": {
      "type": "boolean",
      "title": "Upscale 4X",
      "default": false,
      "x-order": 8,
      "description": "Choose if you want to upscale the image using RealESRGAN 4x"
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 20,
      "minimum": 1,
      "x-order": 4,
      "description": "Number of images to output."
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 3.5,
      "maximum": 20,
      "minimum": 1,
      "x-order": 6,
      "description": "Scale for classifier-free guidance"
    },
    "lora_replicate_link": {
      "type": "string",
      "title": "Lora Replicate Link",
      "x-order": 0,
      "description": "(Optional) Enter your lora replicate link for inference. In case you don't have your own, here is a test link: https://replicate.delivery/pbxt/mu6jfnIIdQWIMKpBXRX3AkRltbjmwEX7kERNInQptcSM3VIJA/output.zip"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 30,
      "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.

Schema

{
  "type": "string",
  "title": "Output",
  "format": "uri"
}