simpletuner/flux-3-klein-image
Public
9
runs
Run simpletuner/flux-3-klein-image with an API
Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.
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 with matching .txt captions.
|
|
| hf_dataset |
string
|
Hugging Face dataset repo ID to use when no archive is provided (e.g., user/dataset).
|
|
| resolution |
None
|
512+1024
|
Training and validation scales; multi-scale sampling preserves aspect ratios.
|
| use_synthetic_regularisation |
boolean
|
True
|
Mix synthetic images into half of training updates to reduce concept bleed into unrelated prompts. Disable to train only on your images.
|
| 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.
|
| train_batch_size |
integer
|
Min: 1 Max: 9 |
Optional batch override. Leave blank for the L40S preset: 9 at 512 and 2 at 1024.
|
| 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
Min: 1 |
Total optimizer updates; the multi-scale 48 GB recipe starts at 4000.
|
| 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/flux3-image/{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": {
"hf_token": {
"type": "string",
"title": "Hf Token",
"format": "password",
"x-order": 23,
"nullable": true,
"writeOnly": true,
"description": "Hugging Face token for downloads and write access when publishing to hub_model_id.",
"x-cog-secret": true
},
"s3_bucket": {
"type": "string",
"title": "S3 Bucket",
"default": "",
"x-order": 15,
"description": "S3-compatible bucket for publishing checkpoints."
},
"s3_region": {
"type": "string",
"title": "S3 Region",
"x-order": 16,
"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": 9
},
"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)."
},
"resolution": {
"enum": [
"512+1024",
"512",
"1024"
],
"type": "string",
"title": "resolution",
"description": "Training and validation scales; multi-scale sampling preserves aspect ratios.",
"default": "512+1024",
"x-order": 2
},
"train_data": {
"type": "string",
"title": "Train Data",
"format": "uri",
"x-order": 0,
"nullable": true,
"description": "Zip or tar of training images with matching .txt captions."
},
"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": 10
},
"enable_crop": {
"type": "boolean",
"title": "Enable Crop",
"default": false,
"x-order": 8,
"description": "Enable cropping when preparing samples."
},
"hf_revision": {
"type": "string",
"title": "Hf Revision",
"x-order": 6,
"nullable": true,
"description": "Optional Hugging Face dataset commit or revision."
},
"return_logs": {
"type": "boolean",
"title": "Return Logs",
"default": true,
"x-order": 24,
"description": "Print the tail of debug.log."
},
"hub_model_id": {
"type": "string",
"title": "Hub Model Id",
"x-order": 22,
"nullable": true,
"description": "Hugging Face model repo for the final LoRA and validation images (e.g., user/model)."
},
"s3_base_path": {
"type": "string",
"title": "S3 Base Path",
"x-order": 18,
"nullable": true,
"description": "Prefix inside the bucket (defaults to cog/flux3-image/{job_id})."
},
"s3_access_key": {
"type": "string",
"title": "S3 Access Key",
"format": "password",
"x-order": 20,
"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": 21,
"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": 1,
"x-order": 14,
"description": "Total optimizer updates; the multi-scale 48 GB recipe starts at 4000."
},
"s3_endpoint_url": {
"type": "string",
"title": "S3 Endpoint Url",
"x-order": 17,
"nullable": true,
"description": "Custom S3 endpoint URL (for non-AWS providers)."
},
"train_batch_size": {
"type": "integer",
"title": "Train Batch Size",
"maximum": 9,
"minimum": 1,
"x-order": 11,
"nullable": true,
"description": "Optional batch override. Leave blank for the L40S preset: 9 at 512 and 2 at 1024."
},
"hf_caption_column": {
"type": "string",
"title": "Hf Caption Column",
"default": "caption",
"x-order": 4,
"description": "Caption column when using hf_dataset."
},
"validation_prompt": {
"type": "string",
"title": "Validation Prompt",
"default": "a detailed photograph, natural lighting",
"x-order": 7,
"description": "Validation prompt; include the concept or trigger you are teaching."
},
"hf_instance_prompt": {
"type": "string",
"title": "Hf Instance Prompt",
"x-order": 5,
"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": 19,
"nullable": true,
"description": "Public base URL to build shareable links (optional)."
},
"checkpoints_total_limit": {
"type": "integer",
"title": "Checkpoints Total Limit",
"default": 5,
"maximum": 5,
"minimum": 1,
"x-order": 12,
"description": "Maximum checkpoints to retain (max 5)."
},
"checkpoint_step_interval": {
"type": "integer",
"title": "Checkpoint Step Interval",
"default": 250,
"minimum": 1,
"x-order": 13,
"description": "Save checkpoints and generate validation images every N optimizer updates."
},
"use_synthetic_regularisation": {
"type": "boolean",
"title": "Use Synthetic Regularisation",
"default": true,
"x-order": 3,
"description": "Mix synthetic images into half of training updates to reduce concept bleed into unrelated prompts. Disable to train only on your images."
}
}
}
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"
}