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MODEL IDrunware:qwen-image@style-lora-training
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Qwen-Image Style LoRA Training

Qwen-Image Style LoRA Training is a Runware training workflow for producing style-focused LoRA adapters on top of the Qwen-Image architecture. It uses a zipped training dataset, a trigger word, and configurable training settings to produce a LoRA safetensors file that can either be downloaded or imported automatically into the platform for later image generation use.

Qwen-Image Style LoRA Training

API Options

Platform-level options for task execution and delivery.

taskType

stringrequiredvalue: training

Identifier for the type of task being performed

taskUUID

stringrequiredUUID v4

UUID v4 identifier for tracking tasks and matching async responses. Must be unique per task.

webhookURL

stringURI

Specifies a webhook URL where JSON responses will be sent via HTTP POST when generation tasks complete. For batch requests with multiple results, each completed item triggers a separate webhook call as it becomes available.

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includeCost

booleandefault: false

Include task cost in the response.

Inputs

Input resources for the task (images, audio, etc). These must be nested inside the inputs object.

inputs » dataset

dataset

stringrequired

Training dataset as a ZIP file (UUID or URL).

Core Parameters

Primary parameters that define the task output.

model

stringrequiredvalue: runware:qwen-image@style-lora-training

Identifier of the model to use for generation.

Learn more3 resources

importModel

objectrequired

Configuration for the trained model that is uploaded to the platform after training completes.

Properties7 properties
importModel » air

air

stringrequiredmin: 1

Artificial Intelligence Resource identifier. Format: provider:model@version.

importModel » heroImageURL

heroImageURL

stringURI

URL of the hero image.

importModel » name

name

stringrequiredmin: 2max: 255

Name of the model.

importModel » private

private

booleandefault: true

Whether the model should be private.

importModel » shortDescription

shortDescription

string

Short description of the model.

importModel » uniqueIdentifier

uniqueIdentifier

stringmin: 1

Unique identifier for the model.

importModel » version

version

stringmin: 1

Version of the model.

learningRate

floatmin: 0.00001max: 0.01default: 0.0005

Step size applied at each training update. Lower values learn more slowly but can improve stability.

trainingSteps

integermin: 10max: 4000default: 300

Total number of optimization steps to run during training.

triggerWord

stringmin: 3max: 100

Word or phrase used to activate the trained concept at inference time.

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