Overview
This schema is used for fine-tuning models with multi image editing capabilities.Schema Type
When creating a fine-tune with this schema, use:script_type:multi_image_editing(the fine-tune type)base_model: One of the supported model canonical names below
Supported Models
- Qwen Image Edit - 2509 (
Qwen/Qwen-Image-Edit-2509) - Qwen Image Edit - 2511 (
Qwen/Qwen-Image-Edit-2511)
Request Schema
Required Fields
| Field | Type | Required | Description |
|---|---|---|---|
batch_size | integer | No | Batch Size (default: 1) (min: 1) |
caption_column | string | Yes | Caption Column (DataFrame column name) |
control_image_columns | array | Yes | Control Image Columns (inputs) (array of string) (Multiple DataFrame column names) |
gradient_accumulation | integer | No | Gradient Accumulation (default: 1) (min: 1) |
image_column | string | Yes | Image Column (output) (DataFrame column name) |
learning_rate | number | No | Learning Rate (default: 0.0002) |
lora_alpha | integer | No | LoRA Alpha (default: 16) (min: 1) |
lora_rank | integer | No | LoRA Rank (default: 16) (min: 1) |
sample_every | integer | No | Sample Every (default: 200) (min: 1) |
sample_height | integer | No | Sample Height (default: 1024) (min: 1) |
sample_width | integer | No | Sample Width (default: 1024) (min: 1) |
samples | array | No | Samples (array of object) |
steps | integer | No | Steps (default: 3000) (min: 1) |
timestep_type | string | No | Timestep Type (options: weighted, sigmoid, linear) |
use_lora | boolean | No | Use LoRA |
Example Request
Field Details
batch_size
Batch Size
Type: integer
Default: 1
Minimum: 1
caption_column
Caption Column
Type: string
Default: ""
control_image_columns
Control Image Columns (inputs)
Type: array
Default: []
gradient_accumulation
Gradient Accumulation
Type: integer
Default: 1
Minimum: 1
image_column
Image Column (output)
Type: string
Default: ""
learning_rate
Learning Rate
Type: number
Default: 0.0002
lora_alpha
LoRA Alpha
Type: integer
Default: 16
Minimum: 1
lora_rank
LoRA Rank
Type: integer
Default: 16
Minimum: 1
sample_every
Sample Every
Type: integer
How often to generate samples during training (n steps)
Default: 200
Minimum: 1
sample_height
Sample Height
Type: integer
Default: 1024
Minimum: 1
sample_width
Sample Width
Type: integer
Default: 1024
Minimum: 1
samples
Samples
Type: array
Used to show progress during the fine-tuning process
Default: [{"ctrl_img_urls": ["https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png", "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"], "prompt": "an ox holding a sign that says 'Oxen.ai'"}, {"ctrl_img_urls": ["https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png", "https://hub.oxen.ai/api/repos/ox/Oxen-Character-Simple-Vector-Graphic/file/main/images/reference/bloxy_white_bg.png"], "prompt": "a herd of oxen running in a field"}]
steps
Steps
Type: integer
Default: 3000
Minimum: 1
timestep_type
Timestep Type
Type: string
Default: "weighted"
Options: weighted, sigmoid, linear
use_lora
Use LoRA
Type: boolean
Default: true