datong-new/qwenimage | API reference

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Run datong-new/qwenimage 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
output_format	None	webp	Output image format
seed	integer		Random seed for reproducible generation. Leave blank for random.
width	integer	512 Min: 512 Max: 2048	width
height	integer	512 Min: 512 Max: 2048	height
prompt	string		Text description of what you want to generate, or the instruction on how to edit the given image.
hf_loras	array		Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux
lora_scales	array		Scale for the LoRA weights. Default value is 0.8
true_cfg_scale	number	2.5 Max: 10	Guidance scale for generation
negative_prompt	string		Text description of what you do not want to generate, or the instruction on how to edit the given image.
num_inference_steps	integer	28 Min: 4 Max: 50	Number of inference steps

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt",
    "negative_prompt"
  ],
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "nullable": true,
      "description": "Random seed for reproducible generation. Leave blank for random."
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 512,
      "maximum": 2048,
      "minimum": 512,
      "description": "width"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 512,
      "maximum": 2048,
      "minimum": 512,
      "description": "height"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "description": "Text description of what you want to generate, or the instruction on how to edit the given image."
    },
    "hf_loras": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Hf Loras",
      "nullable": true,
      "description": "Huggingface path, or URL to the LoRA weights. Ex: alvdansen/frosting_lane_flux"
    },
    "lora_scales": {
      "type": "array",
      "items": {
        "type": "number"
      },
      "title": "Lora Scales",
      "nullable": true,
      "description": "Scale for the LoRA weights. Default value is 0.8"
    },
    "output_format": {
      "enum": [
        "webp",
        "jpg",
        "png"
      ],
      "type": "string",
      "title": "output_format",
      "description": "Output image format",
      "default": "webp",
      "x-order": 6
    },
    "true_cfg_scale": {
      "type": "number",
      "title": "True Cfg Scale",
      "default": 2.5,
      "maximum": 10,
      "minimum": 0,
      "description": "Guidance scale for generation"
    },
    "negative_prompt": {
      "type": "string",
      "title": "Negative Prompt",
      "description": "Text description of what you do not want to generate, or the instruction on how to edit the given image."
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 28,
      "maximum": 50,
      "minimum": 4,
      "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"
}