lightweight-ai/z-l-t-1
Public
5
runs
Run lightweight-ai/z-l-t-1 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 |
|---|---|---|---|
| lr |
number
|
0.0001
|
train.lr
|
| conv |
integer
|
-1
|
network.conv override (-1이면 템플릿 유지)
|
| name |
string
|
|
cfg.config.name
|
| seed |
integer
|
0
|
sample.seed (0이면 무시)
|
| steps |
integer
|
3000
|
train.steps
|
| linear |
integer
|
-1
|
network.linear override (-1이면 템플릿 유지)
|
| prompts |
string
|
|
샘플 프롬프트들. 줄바꿈으로 여러 개 입력 가능. 비우면 템플릿 값 사용
|
| quantize |
boolean
|
True
|
model.quantize override
|
| batch_size |
integer
|
1
|
train.batch_size
|
| conv_alpha |
integer
|
-1
|
network.conv_alpha override (-1이면 템플릿 유지)
|
| resolution |
string
|
|
예: '1024,1280,1536' 형태. 비우면 템플릿 값 사용
|
| dataset_zip |
string
|
학습 이미지 zip (선택). 제공하면 dataset_folder로 안전 추출합니다.
|
|
| quantize_te |
boolean
|
True
|
model.quantize_te override
|
| linear_alpha |
integer
|
-1
|
network.linear_alpha override (-1이면 템플릿 유지)
|
| sample_every |
integer
|
0
|
sample.sample_every (0이면 무시)
|
| sample_steps |
integer
|
0
|
sample.sample_steps (0이면 무시)
|
| sample_width |
integer
|
0
|
sample.width (0이면 무시)
|
| trigger_word |
string
|
parkboyoung2
|
trigger word (caption 기본값)
|
| output_subdir |
string
|
|
output 하위 폴더명
|
| sample_height |
integer
|
0
|
sample.height (0이면 무시)
|
| dataset_folder |
string
|
|
datasets 폴더 내 서브폴더명 또는 절대경로. 비우면 DEFAULT_DATASET_FOLDER 사용
|
| dataset_images |
array
|
[]
|
학습 이미지 파일들(여러 개 업로드 가능). zip 대신 사용 가능
|
| guidance_scale |
number
|
-1
|
sample.guidance_scale (-1이면 무시)
|
| clear_dataset_dir |
boolean
|
False
|
dataset_zip/dataset_images를 넣기 전에 기존 dataset_folder를 비울지 여부
|
| model_name_or_path |
string
|
Tongyi-MAI/Z-Image-Turbo
|
model.name_or_path override
|
| gradient_accumulation |
integer
|
1
|
train.gradient_accumulation
|
{
"type": "object",
"title": "Input",
"properties": {
"lr": {
"type": "number",
"title": "Lr",
"default": 0.0001,
"description": "train.lr"
},
"conv": {
"type": "integer",
"title": "Conv",
"default": -1,
"description": "network.conv override (-1\uc774\uba74 \ud15c\ud50c\ub9bf \uc720\uc9c0)"
},
"name": {
"type": "string",
"title": "Name",
"default": "",
"description": "cfg.config.name"
},
"seed": {
"type": "integer",
"title": "Seed",
"default": 0,
"description": "sample.seed (0\uc774\uba74 \ubb34\uc2dc)"
},
"steps": {
"type": "integer",
"title": "Steps",
"default": 3000,
"description": "train.steps"
},
"linear": {
"type": "integer",
"title": "Linear",
"default": -1,
"description": "network.linear override (-1\uc774\uba74 \ud15c\ud50c\ub9bf \uc720\uc9c0)"
},
"prompts": {
"type": "string",
"title": "Prompts",
"default": "",
"description": "\uc0d8\ud50c \ud504\ub86c\ud504\ud2b8\ub4e4. \uc904\ubc14\uafc8\uc73c\ub85c \uc5ec\ub7ec \uac1c \uc785\ub825 \uac00\ub2a5. \ube44\uc6b0\uba74 \ud15c\ud50c\ub9bf \uac12 \uc0ac\uc6a9"
},
"quantize": {
"type": "boolean",
"title": "Quantize",
"default": true,
"description": "model.quantize override"
},
"batch_size": {
"type": "integer",
"title": "Batch Size",
"default": 1,
"description": "train.batch_size"
},
"conv_alpha": {
"type": "integer",
"title": "Conv Alpha",
"default": -1,
"description": "network.conv_alpha override (-1\uc774\uba74 \ud15c\ud50c\ub9bf \uc720\uc9c0)"
},
"resolution": {
"type": "string",
"title": "Resolution",
"default": "",
"description": "\uc608: '1024,1280,1536' \ud615\ud0dc. \ube44\uc6b0\uba74 \ud15c\ud50c\ub9bf \uac12 \uc0ac\uc6a9"
},
"dataset_zip": {
"type": "string",
"title": "Dataset Zip",
"format": "uri",
"description": "\ud559\uc2b5 \uc774\ubbf8\uc9c0 zip (\uc120\ud0dd). \uc81c\uacf5\ud558\uba74 dataset_folder\ub85c \uc548\uc804 \ucd94\ucd9c\ud569\ub2c8\ub2e4."
},
"quantize_te": {
"type": "boolean",
"title": "Quantize Te",
"default": true,
"description": "model.quantize_te override"
},
"linear_alpha": {
"type": "integer",
"title": "Linear Alpha",
"default": -1,
"description": "network.linear_alpha override (-1\uc774\uba74 \ud15c\ud50c\ub9bf \uc720\uc9c0)"
},
"sample_every": {
"type": "integer",
"title": "Sample Every",
"default": 0,
"description": "sample.sample_every (0\uc774\uba74 \ubb34\uc2dc)"
},
"sample_steps": {
"type": "integer",
"title": "Sample Steps",
"default": 0,
"description": "sample.sample_steps (0\uc774\uba74 \ubb34\uc2dc)"
},
"sample_width": {
"type": "integer",
"title": "Sample Width",
"default": 0,
"description": "sample.width (0\uc774\uba74 \ubb34\uc2dc)"
},
"trigger_word": {
"type": "string",
"title": "Trigger Word",
"default": "parkboyoung2",
"description": "trigger word (caption \uae30\ubcf8\uac12)"
},
"output_subdir": {
"type": "string",
"title": "Output Subdir",
"default": "",
"description": "output \ud558\uc704 \ud3f4\ub354\uba85"
},
"sample_height": {
"type": "integer",
"title": "Sample Height",
"default": 0,
"description": "sample.height (0\uc774\uba74 \ubb34\uc2dc)"
},
"dataset_folder": {
"type": "string",
"title": "Dataset Folder",
"default": "",
"description": "datasets \ud3f4\ub354 \ub0b4 \uc11c\ube0c\ud3f4\ub354\uba85 \ub610\ub294 \uc808\ub300\uacbd\ub85c. \ube44\uc6b0\uba74 DEFAULT_DATASET_FOLDER \uc0ac\uc6a9"
},
"dataset_images": {
"type": "array",
"items": {
"type": "string",
"format": "uri"
},
"title": "Dataset Images",
"default": [],
"description": "\ud559\uc2b5 \uc774\ubbf8\uc9c0 \ud30c\uc77c\ub4e4(\uc5ec\ub7ec \uac1c \uc5c5\ub85c\ub4dc \uac00\ub2a5). zip \ub300\uc2e0 \uc0ac\uc6a9 \uac00\ub2a5"
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": -1,
"description": "sample.guidance_scale (-1\uc774\uba74 \ubb34\uc2dc)"
},
"clear_dataset_dir": {
"type": "boolean",
"title": "Clear Dataset Dir",
"default": false,
"description": "dataset_zip/dataset_images\ub97c \ub123\uae30 \uc804\uc5d0 \uae30\uc874 dataset_folder\ub97c \ube44\uc6b8\uc9c0 \uc5ec\ubd80"
},
"model_name_or_path": {
"type": "string",
"title": "Model Name Or Path",
"default": "Tongyi-MAI/Z-Image-Turbo",
"description": "model.name_or_path override"
},
"gradient_accumulation": {
"type": "integer",
"title": "Gradient Accumulation",
"default": 1,
"description": "train.gradient_accumulation"
}
}
}
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"
}