Z-Image LoRA Trainer: Training

Train custom image LoRA models with Z-Image LoRA Trainer. Fast dataset training with zip uploads and auto-tuned defaults. Try free on Muapi. Train custom image LoRA models from your dataset with zip uploads, auto-tuned defaults, and fast iteration for brand, character, or IP looks.

Interactive model controls

Train custom image LoRA models from your dataset with zip uploads, auto-tuned defaults, and fast iteration for brand, character, or IP looks.

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Overview

About this model

Z-Image LoRA Trainer enables creators and developers to train custom image LoRA adapters directly from their own datasets. Simply upload a zip archive containing training images along with optional text caption files to fine-tune your target style, character, or brand identity. With fast training iterations, auto-tuned hyperparameters, customizable training steps from 1,000 to 10,000, adjustable learning rates, and flexible LoRA rank configurations, Z-Image LoRA Trainer provides full control over high-fidelity LoRA creation.

1Character Fine-Tuning: Train custom LoRA models on specific character designs and consistent digital personas.

2Brand & Style Adaptation: Teach the model visual brand identities, color palettes, and artistic styles.

3Object & IP Training: Create targeted LoRA adapters for proprietary products, icons, and intellectual property.

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Pricing & Value

Cost analysis

Provider	Cost	Notes
muapiapp	$2.50 per 1,000 steps	Pay per training step with auto-tuned defaults and zero setup overhead.
Fal.ai	Not available	Z-Image LoRA Trainer is not hosted on Fal.ai.
Replicate	Not available	Z-Image LoRA Trainer is not hosted on Replicate.

muapiapp$2.50 per 1,000 steps

Pay per training step with auto-tuned defaults and zero setup overhead.

Fal.aiNot available

Z-Image LoRA Trainer is not hosted on Fal.ai.

ReplicateNot available

Z-Image LoRA Trainer is not hosted on Replicate.

** Competitor pricing is estimated based on similar model architectures and usage tiers.

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Technical Details

Configuration schema

Parameter	Type	Description	Default
Dataset Zip URL	string	URL to zip archive with images. Try to use at least 4 images in general the more the better. In addition to images the archive can contain text files with captions.	`undefined`
Trigger Word	string	Optional trigger word. If a caption file exists, it is prepended when not already present.	`example`
Steps	int	Number of steps to train the LoRA on.	`1000`
Learning Rate	float	Learning rate for LoRA training.	`0.0001`
LoRA Rank	int	LoRA rank dimension.	`16`

Dataset Zip URLstring

URL to zip archive with images. Try to use at least 4 images in general the more the better. In addition to images the archive can contain text files with captions.

Default Valueundefined

Trigger Wordstring

Optional trigger word. If a caption file exists, it is prepended when not already present.

Default Valueexample

Stepsint

Number of steps to train the LoRA on.

Default Value1000

Learning Ratefloat

Learning rate for LoRA training.

Default Value0.0001

LoRA Rankint

LoRA rank dimension.

Default Value16

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Implementation Guide

Developer documentation

How to Use Z-Image LoRA Trainer API

Prepare your dataset: Create a .zip archive containing at least 4-10 high-quality images. Optionally include .txt files with matching filenames for text captions.
Set training parameters: Specify optional parameters such as trigger_word, steps (default 1000), learning_rate (default 0.0001), and lora_rank (default 16).
Submit the request via API:

curl -X POST "https://api.muapi.ai/api/v1/z-image-lora-trainer" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "data": "https://example.com/my-dataset.zip",
    "trigger_word": "my_custom_style",
    "steps": 1000,
    "learning_rate": 0.0001,
    "lora_rank": 16
  }'

Retrieve your model: The API returns a request_id. Once training completes, the webhook or result URL will provide the generated LoRA weights output.

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Common Questions

Frequently asked

What is Z-Image LoRA Trainer?

Z-Image LoRA Trainer is an asynchronous REST API that allows you to train custom image LoRA adapters from a zipped image dataset with automated defaults and customizable hyperparameter settings.

How should I structure the dataset zip archive?

Upload a `.zip` file containing image files (PNG/JPEG/WebP). To include custom captions, add `.txt` files with the exact same base filename as each corresponding image file.

What is a trigger word and how is it used?

A trigger word is a unique token prepended to training captions. When generating images with your trained LoRA, including this trigger word activates the specific learned character, object, or style.

How many steps should I use for training?

The default setting is 1,000 steps, which works well for most datasets. You can adjust training steps between 1,000 and 10,000 depending on your dataset size and desired fidelity.

What output format is generated upon completion?

Once training is complete, the API output contains a URL to download the trained LoRA model weights file ready for inference.