Fine-Tune: Image Generation

Fine-tune a model to generate an image from text

Overview

This schema is used for fine-tuning models with image generation capabilities.

Schema Type

When creating a fine-tune with this schema, use:

{
  "resource": "main/your-dataset.parquet",
  "base_model": "<model-canonical-name>",
  "script_type": "image_generation",
  "training_params": {
    ...
  }
}

Key Parameters:

• script_type: image_generation (the fine-tune type)
• base_model: One of the supported model canonical names below

Supported Models

• Qwen Image (Qwen/Qwen-Image)
• FLUX.1 [dev] (black-forest-labs/FLUX.1-dev)
• FLUX.2 [dev] (black-forest-labs/FLUX.2-dev)
• Z-Image-Turbo (Tongyi-MAI/Z-Image-Turbo)

Request Schema

Required Fields

Field	Type	Required	Description
batch_size	integer	No	(default: 1) (min: 1)
caption_column	string	Yes	caption_column (DataFrame column name)
gradient_accumulation	integer	No	(default: 1) (min: 1)
image_column	string	Yes	image_column (DataFrame column name)
learning_rate	number	No	(default: 0.0002)
lora_alpha	integer	No	(default: 16) (min: 1)
lora_rank	integer	No	(default: 16) (min: 1)
sample_every	integer	No	(default: 200) (min: 1)
samples	array	No	(array of object)
steps	integer	No	(default: 2000) (min: 1)
timestep_type	string	No	(options: weighted, sigmoid, linear)
use_lora	boolean	No	use_lora

Example Request

Request Body

{
  "resource": "main/your-dataset.parquet",
  "base_model": "<model-canonical-name>",
  "script_type": "image_generation",
  "training_params": {
    "batch_size": 1,
    "caption_column": "",
    "gradient_accumulation": 1,
    "image_column": "",
    "learning_rate": 0.0002,
    "lora_alpha": 16,
    "lora_rank": 16,
    "sample_every": 200,
    "samples": [
      {
        "prompt": "an ox holding a sign that says 'Oxen.ai'"
      },
      {
        "prompt": "a herd of oxen running in a field"
      }
    ],
    "steps": 2000,
    "timestep_type": "sigmoid",
    "use_lora": true
  }
}

import requests

url = "https://hub.oxen.ai/api/repos/{namespace}/{repo_name}/fine_tunes"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

data = {{
  "resource": "main/your-dataset.parquet",
  "base_model": "<model-canonical-name>",
  "script_type": "image_generation",
  "training_params": {{
    "batch_size": 1,
    "caption_column": "",
    "gradient_accumulation": 1,
    "image_column": "",
    "learning_rate": 0.0002,
    "lora_alpha": 16,
    "lora_rank": 16,
    "sample_every": 200,
    "samples": [
      {{
        "prompt": "an ox holding a sign that says 'Oxen.ai'"
      }},
      {{
        "prompt": "a herd of oxen running in a field"
      }}
    ],
    "steps": 2000,
    "timestep_type": "sigmoid",
    "use_lora": true
  }}
}}

response = requests.post(url, headers=headers, json=data)
print(response.json())

curl -X POST https://hub.oxen.ai/api/repos/{namespace}/{repo_name}/fine_tunes \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{   "resource": "main/your-dataset.parquet",   "base_model": "<model-canonical-name>",   "script_type": "image_generation",   "training_params": {     "batch_size": 1,     "caption_column": "",     "gradient_accumulation": 1,     "image_column": "",     "learning_rate": 0.0002,     "lora_alpha": 16,     "lora_rank": 16,     "sample_every": 200,     "samples": [       {         "prompt": "an ox holding a sign that says 'Oxen.ai'"       },       {         "prompt": "a herd of oxen running in a field"       }     ],     "steps": 2000,     "timestep_type": "sigmoid",     "use_lora": true   } }'

Field Details

batch_size

Type: integer

Default: 1

Minimum: 1

caption_column

Type: string

Default: ""

gradient_accumulation

Type: integer

Default: 1

Minimum: 1

image_column

Type: string

Default: ""

learning_rate

Type: number

Default: 0.0002

lora_alpha

Type: integer

Default: 16

Minimum: 1

lora_rank

Type: integer

Default: 16

Minimum: 1

sample_every

Type: integer

Default: 200

Minimum: 1

samples

Type: array

Default: [{"prompt": "an ox holding a sign that says 'Oxen.ai'"}, {"prompt": "a herd of oxen running in a field"}]

steps

Type: integer

Default: 2000

Minimum: 1

timestep_type

Type: string

Default: "sigmoid"

Options: weighted, sigmoid, linear

use_lora

Type: boolean

Default: true