lightweight-ai/model2_9 – API reference

lightweight-ai / model2_9

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Run lightweight-ai/model2_9 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 fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.	Prompt for generated image
image	string		Upload an image for inpainting. This will be the base image that will be partially modified.
inpaint	boolean	False	Prompt for generated image
mask	string		Upload a mask image for inpainting. White areas (255) indicate regions to be inpainted, while black areas (0) will be preserved from the original image.
width	integer	1024	Width of output image
height	integer	1024	Height of output image
prompt_strength	number	0.8 Max: 1	Prompt strength (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image.
num_outputs	integer	1 Min: 1 Max: 4	Number of images to output.
num_inference_steps	integer	28 Min: 1 Max: 50	Number of inference steps
loras	array	[]	Lora list (Realism, Karina, IU)
lora_scales	array	[]	Lora scales
seed	integer		Random seed. Set for reproducible generation
output_format	string (enum)	png Options: webp, jpg, png	Format of the output images
output_quality	integer	100 Max: 100	Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs

{
  "type": "object",
  "title": "Input",
  "properties": {
    "mask": {
      "type": "string",
      "title": "Mask",
      "format": "uri",
      "x-order": 3,
      "description": "Upload a mask image for inpainting. White areas (255) indicate regions to be inpainted, while black areas (0) will be preserved from the original image."
    },
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 11,
      "description": "Random seed. Set for reproducible generation"
    },
    "image": {
      "type": "string",
      "title": "Image",
      "format": "uri",
      "x-order": 1,
      "description": "Upload an image for inpainting. This will be the base image that will be partially modified."
    },
    "loras": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Loras",
      "default": [],
      "x-order": 9,
      "description": "Lora list (Realism, Karina, IU)"
    },
    "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": "A fluffy, orange tabby cat curled up asleep in a sunbeam streaming through a window, its soft fur glowing with the warmth of the light; highly detailed 8K UHD photorealistic rendering, natural lighting, warm and inviting atmosphere, focus on softness and texture.",
      "x-order": 0,
      "description": "Prompt for generated image"
    },
    "inpaint": {
      "type": "boolean",
      "title": "Inpaint",
      "default": false,
      "x-order": 2,
      "description": "Prompt for generated image"
    },
    "lora_scales": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "title": "Lora Scales",
      "default": [],
      "x-order": 10,
      "description": "Lora scales"
    },
    "num_outputs": {
      "type": "integer",
      "title": "Num Outputs",
      "default": 1,
      "maximum": 4,
      "minimum": 1,
      "x-order": 7,
      "description": "Number of images to output."
    },
    "output_format": {
      "enum": [
        "webp",
        "jpg",
        "png"
      ],
      "type": "string",
      "title": "output_format",
      "description": "Format of the output images",
      "default": "png",
      "x-order": 12
    },
    "output_quality": {
      "type": "integer",
      "title": "Output Quality",
      "default": 100,
      "maximum": 100,
      "minimum": 0,
      "x-order": 13,
      "description": "Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs"
    },
    "prompt_strength": {
      "type": "number",
      "title": "Prompt Strength",
      "default": 0.8,
      "maximum": 1,
      "minimum": 0,
      "x-order": 6,
      "description": "Prompt strength (or denoising strength) when using image to image. 1.0 corresponds to full destruction of information in image."
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 28,
      "maximum": 50,
      "minimum": 1,
      "x-order": 8,
      "description": "Number of inference 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"
}