ddvinh1/text2image-1.3b | API reference

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Run ddvinh1/text2image-1.3b 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		Text prompt for image generation
negative_prompt	string	Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards	Negative prompt to avoid unwanted elements
width	integer	1024 Min: 480 Max: 1280	Width of the output image
height	integer	1024 Min: 480 Max: 1280	Height of the output image
num_inference_steps	integer	30 Min: 1 Max: 80	Number of inference steps. More steps = higher quality but slower
guidance_scale	number	1 Max: 10	Guidance scale for classifier-free guidance
lora_id	string		Optional: Hugging Face LoRA ID for custom styling (e.g., 'username/lora-name')

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt"
  ],
  "properties": {
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 1024,
      "maximum": 1280,
      "minimum": 480,
      "x-order": 2,
      "description": "Width of the output image"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 1024,
      "maximum": 1280,
      "minimum": 480,
      "x-order": 3,
      "description": "Height of the output image"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Text prompt for image generation"
    },
    "lora_id": {
      "type": "string",
      "title": "Lora Id",
      "default": "",
      "x-order": 6,
      "description": "Optional: Hugging Face LoRA ID for custom styling (e.g., 'username/lora-name')"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 1,
      "maximum": 10,
      "minimum": 0,
      "x-order": 5,
      "description": "Guidance scale for classifier-free guidance"
    },
    "negative_prompt": {
      "type": "string",
      "title": "Negative Prompt",
      "default": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
      "x-order": 1,
      "description": "Negative prompt to avoid unwanted elements"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 30,
      "maximum": 80,
      "minimum": 1,
      "x-order": 4,
      "description": "Number of inference steps. More steps = higher quality but slower"
    }
  }
}

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"
}