simpletuner/z-image
Public
28
runs
Run simpletuner/z-image with an API
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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 |
|---|---|---|---|
| train_data |
string
|
Zip or tar of training images. Matching .txt captions are preserved; missing captions use the trigger and filename.
|
|
| hf_dataset |
string
|
Hugging Face dataset repo ID to use when no archive is provided (e.g., user/dataset).
|
|
| model |
None
|
Z-Image-Turbo
|
Training assistant version for Z-Image Turbo. v1 preserves the original recipe.
|
| resolution |
None
|
1024
|
Training and validation scales; multi-scale sampling preserves aspect ratios.
|
| use_synthetic_regularisation |
boolean
|
False
|
Mix synthetic images into half of training updates. Available at 512 and 1024 resolutions.
|
| hf_caption_column |
string
|
caption
|
Caption column when using hf_dataset.
|
| hf_instance_prompt |
string
|
Use this caption for every Hugging Face image instead of a caption column. Include your trigger.
|
|
| hf_revision |
string
|
Optional Hugging Face dataset commit or revision.
|
|
| validation_prompt |
string
|
a detailed photograph, natural lighting
|
Validation prompt; include the concept or trigger you are teaching.
|
| enable_crop |
boolean
|
False
|
Enable cropping when preparing samples.
|
| crop_style |
None
|
center
|
Crop location style when cropping is enabled.
|
| crop_aspect |
None
|
preserve
|
Aspect handling for crops: square (1:1) or preserve source aspect.
|
| trigger_word |
string
|
TOK
|
Subject token used in generated fallback captions and instance prompts.
|
| caption_strategy |
None
|
textfile
|
Captions for uploaded images: matching text files with filename fallbacks, filenames, or one instance prompt.
|
| train_batch_size |
integer
|
2
Min: 1 Max: 4 |
Training batch size (1-4).
|
| checkpoints_total_limit |
integer
|
5
Min: 1 Max: 5 |
Maximum checkpoints to retain (max 5).
|
| checkpoint_step_interval |
integer
|
250
Min: 1 |
Save checkpoints and generate validation images every N optimizer updates.
|
| max_train_steps |
integer
|
4000
|
Total optimizer updates. Regularisation updates count toward this limit.
|
| learning_rate |
number
|
Min: 0.00000001 Max: 0.01 |
Learning rate. Leave blank for the model recipe.
|
| lora_rank |
integer
|
Min: 1 Max: 256 |
Adapter rank; alpha matches rank. Leave blank for rank 64.
|
| lora_dropout |
number
|
0
Max: 0.999 |
Adapter dropout probability.
|
| seed |
integer
|
42
|
Training and validation seed.
|
| attention_mechanism |
None
|
kohaku-fa-auto
|
Automatic centered Kohaku attention, or native Diffusers attention.
|
| gradient_checkpointing_interval |
integer
|
Min: 1 Max: 64 |
Blocks per checkpointed segment. Leave blank for the model recipe.
|
| gradient_checkpointing_segment_stride |
integer
|
Min: 1 Max: 64 |
Start a checkpointed segment every N blocks. Leave blank for contiguous segments.
|
| regional_compile |
boolean
|
True
|
Compile repeated transformer blocks.
|
| dataloader_prefetch |
boolean
|
True
|
Prepare the next training batches in the background.
|
| push_checkpoints_to_hub |
boolean
|
True
|
Upload retained intermediate checkpoints as well as final weights when hub_model_id is set.
|
| pixel_area |
integer
|
Min: 256 Max: 2048 |
Legacy single-resolution override. Prefer resolution for new jobs.
|
| num_train_epochs |
integer
|
Min: 1 |
Legacy epoch limit, used with max_train_steps=0.
|
| checkpoint_epoch_interval |
integer
|
Min: 1 |
Optional epoch-based checkpoint interval.
|
| s3_bucket |
string
|
|
S3-compatible bucket for publishing checkpoints.
|
| s3_region |
string
|
S3 region (optional).
|
|
| s3_endpoint_url |
string
|
Custom S3 endpoint URL (for non-AWS providers).
|
|
| s3_base_path |
string
|
Prefix inside the bucket (defaults to cog/zimage/{job_id}).
|
|
| s3_public_base_url |
string
|
Public base URL to build shareable links (optional).
|
|
| s3_access_key |
string
|
S3 access key (leave blank to use IAM/instance roles).
|
|
| s3_secret_key |
string
|
S3 secret key (leave blank to use IAM/instance roles).
|
|
| hub_model_id |
string
|
Hugging Face model repo for the final LoRA and validation images (e.g., user/model).
|
|
| hf_token |
string
|
Hugging Face token for downloads and write access when publishing to hub_model_id.
|
|
| return_logs |
boolean
|
True
|
Print the tail of debug.log.
|
{
"type": "object",
"title": "Input",
"properties": {
"seed": {
"type": "integer",
"title": "Seed",
"default": 42,
"minimum": 0,
"x-order": 21,
"description": "Training and validation seed."
},
"model": {
"enum": [
"Z-Image-Turbo",
"Z-Image-Turbo-v2"
],
"type": "string",
"title": "model",
"description": "Training assistant version for Z-Image Turbo. v1 preserves the original recipe.",
"default": "Z-Image-Turbo",
"x-order": 2
},
"hf_token": {
"type": "string",
"title": "Hf Token",
"format": "password",
"x-order": 39,
"nullable": true,
"writeOnly": true,
"description": "Hugging Face token for downloads and write access when publishing to hub_model_id.",
"x-cog-secret": true
},
"lora_rank": {
"type": "integer",
"title": "Lora Rank",
"maximum": 256,
"minimum": 1,
"x-order": 19,
"nullable": true,
"description": "Adapter rank; alpha matches rank. Leave blank for rank 64."
},
"s3_bucket": {
"type": "string",
"title": "S3 Bucket",
"default": "",
"x-order": 31,
"description": "S3-compatible bucket for publishing checkpoints."
},
"s3_region": {
"type": "string",
"title": "S3 Region",
"x-order": 32,
"nullable": true,
"description": "S3 region (optional)."
},
"crop_style": {
"enum": [
"center",
"random"
],
"type": "string",
"title": "crop_style",
"description": "Crop location style when cropping is enabled.",
"default": "center",
"x-order": 10
},
"hf_dataset": {
"type": "string",
"title": "Hf Dataset",
"x-order": 1,
"nullable": true,
"description": "Hugging Face dataset repo ID to use when no archive is provided (e.g., user/dataset)."
},
"pixel_area": {
"type": "integer",
"title": "Pixel Area",
"maximum": 2048,
"minimum": 256,
"x-order": 28,
"nullable": true,
"description": "Legacy single-resolution override. Prefer resolution for new jobs."
},
"resolution": {
"enum": [
"512+1024",
"256",
"512",
"768",
"1024",
"1536",
"2048"
],
"type": "string",
"title": "resolution",
"description": "Training and validation scales; multi-scale sampling preserves aspect ratios.",
"default": "1024",
"x-order": 3
},
"train_data": {
"type": "string",
"title": "Train Data",
"format": "uri",
"x-order": 0,
"nullable": true,
"description": "Zip or tar of training images. Matching .txt captions are preserved; missing captions use the trigger and filename."
},
"crop_aspect": {
"enum": [
"square",
"preserve"
],
"type": "string",
"title": "crop_aspect",
"description": "Aspect handling for crops: square (1:1) or preserve source aspect.",
"default": "preserve",
"x-order": 11
},
"enable_crop": {
"type": "boolean",
"title": "Enable Crop",
"default": false,
"x-order": 9,
"description": "Enable cropping when preparing samples."
},
"hf_revision": {
"type": "string",
"title": "Hf Revision",
"x-order": 7,
"nullable": true,
"description": "Optional Hugging Face dataset commit or revision."
},
"return_logs": {
"type": "boolean",
"title": "Return Logs",
"default": true,
"x-order": 40,
"description": "Print the tail of debug.log."
},
"hub_model_id": {
"type": "string",
"title": "Hub Model Id",
"x-order": 38,
"nullable": true,
"description": "Hugging Face model repo for the final LoRA and validation images (e.g., user/model)."
},
"lora_dropout": {
"type": "number",
"title": "Lora Dropout",
"default": 0,
"maximum": 0.999,
"minimum": 0,
"x-order": 20,
"description": "Adapter dropout probability."
},
"s3_base_path": {
"type": "string",
"title": "S3 Base Path",
"x-order": 34,
"nullable": true,
"description": "Prefix inside the bucket (defaults to cog/zimage/{job_id})."
},
"trigger_word": {
"type": "string",
"title": "Trigger Word",
"default": "TOK",
"x-order": 12,
"description": "Subject token used in generated fallback captions and instance prompts."
},
"learning_rate": {
"type": "number",
"title": "Learning Rate",
"maximum": 0.01,
"minimum": 1e-08,
"x-order": 18,
"nullable": true,
"description": "Learning rate. Leave blank for the model recipe."
},
"s3_access_key": {
"type": "string",
"title": "S3 Access Key",
"format": "password",
"x-order": 36,
"nullable": true,
"writeOnly": true,
"description": "S3 access key (leave blank to use IAM/instance roles).",
"x-cog-secret": true
},
"s3_secret_key": {
"type": "string",
"title": "S3 Secret Key",
"format": "password",
"x-order": 37,
"nullable": true,
"writeOnly": true,
"description": "S3 secret key (leave blank to use IAM/instance roles).",
"x-cog-secret": true
},
"max_train_steps": {
"type": "integer",
"title": "Max Train Steps",
"default": 4000,
"minimum": 0,
"x-order": 17,
"description": "Total optimizer updates. Regularisation updates count toward this limit."
},
"s3_endpoint_url": {
"type": "string",
"title": "S3 Endpoint Url",
"x-order": 33,
"nullable": true,
"description": "Custom S3 endpoint URL (for non-AWS providers)."
},
"caption_strategy": {
"enum": [
"textfile",
"filename",
"instanceprompt"
],
"type": "string",
"title": "caption_strategy",
"description": "Captions for uploaded images: matching text files with filename fallbacks, filenames, or one instance prompt.",
"default": "textfile",
"x-order": 13
},
"num_train_epochs": {
"type": "integer",
"title": "Num Train Epochs",
"minimum": 1,
"x-order": 29,
"nullable": true,
"description": "Legacy epoch limit, used with max_train_steps=0."
},
"regional_compile": {
"type": "boolean",
"title": "Regional Compile",
"default": true,
"x-order": 25,
"description": "Compile repeated transformer blocks."
},
"train_batch_size": {
"type": "integer",
"title": "Train Batch Size",
"default": 2,
"maximum": 4,
"minimum": 1,
"x-order": 14,
"description": "Training batch size (1-4)."
},
"hf_caption_column": {
"type": "string",
"title": "Hf Caption Column",
"default": "caption",
"x-order": 5,
"description": "Caption column when using hf_dataset."
},
"validation_prompt": {
"type": "string",
"title": "Validation Prompt",
"default": "a detailed photograph, natural lighting",
"x-order": 8,
"description": "Validation prompt; include the concept or trigger you are teaching."
},
"hf_instance_prompt": {
"type": "string",
"title": "Hf Instance Prompt",
"x-order": 6,
"nullable": true,
"description": "Use this caption for every Hugging Face image instead of a caption column. Include your trigger."
},
"s3_public_base_url": {
"type": "string",
"title": "S3 Public Base Url",
"x-order": 35,
"nullable": true,
"description": "Public base URL to build shareable links (optional)."
},
"attention_mechanism": {
"enum": [
"kohaku-fa-auto",
"diffusers"
],
"type": "string",
"title": "attention_mechanism",
"description": "Automatic centered Kohaku attention, or native Diffusers attention.",
"default": "kohaku-fa-auto",
"x-order": 22
},
"dataloader_prefetch": {
"type": "boolean",
"title": "Dataloader Prefetch",
"default": true,
"x-order": 26,
"description": "Prepare the next training batches in the background."
},
"checkpoints_total_limit": {
"type": "integer",
"title": "Checkpoints Total Limit",
"default": 5,
"maximum": 5,
"minimum": 1,
"x-order": 15,
"description": "Maximum checkpoints to retain (max 5)."
},
"push_checkpoints_to_hub": {
"type": "boolean",
"title": "Push Checkpoints To Hub",
"default": true,
"x-order": 27,
"description": "Upload retained intermediate checkpoints as well as final weights when hub_model_id is set."
},
"checkpoint_step_interval": {
"type": "integer",
"title": "Checkpoint Step Interval",
"default": 250,
"minimum": 1,
"x-order": 16,
"description": "Save checkpoints and generate validation images every N optimizer updates."
},
"checkpoint_epoch_interval": {
"type": "integer",
"title": "Checkpoint Epoch Interval",
"minimum": 1,
"x-order": 30,
"nullable": true,
"description": "Optional epoch-based checkpoint interval."
},
"use_synthetic_regularisation": {
"type": "boolean",
"title": "Use Synthetic Regularisation",
"default": false,
"x-order": 4,
"description": "Mix synthetic images into half of training updates. Available at 512 and 1024 resolutions."
},
"gradient_checkpointing_interval": {
"type": "integer",
"title": "Gradient Checkpointing Interval",
"maximum": 64,
"minimum": 1,
"x-order": 23,
"nullable": true,
"description": "Blocks per checkpointed segment. Leave blank for the model recipe."
},
"gradient_checkpointing_segment_stride": {
"type": "integer",
"title": "Gradient Checkpointing Segment Stride",
"maximum": 64,
"minimum": 1,
"x-order": 24,
"nullable": true,
"description": "Start a checkpointed segment every N blocks. Leave blank for contiguous segments."
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{
"type": "string",
"title": "Output",
"format": "uri"
}