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alexgenovese /train-sdxl-kohya:a0b4df0a
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 |
---|---|---|---|
pretrained_model_name_or_path |
string
|
stabilityai/stable-diffusion-xl-base-1.0
|
base model name or path
|
train_data_zip |
string
|
Upload image dataset in zip format using this naming convention: XX_token className.zip
|
|
network_weights |
string
|
Pretrained LoRA weights
|
|
output_name |
string
|
new_model_name
|
Model name
|
save_model_as |
string
(enum)
|
safetensors
Options: ckpt, pt, safetensors |
model save extension | ckpt, pt, safetensors
|
resolution |
string
|
1024
|
image resolution must be 'size' or 'width,height'.
|
batch_size |
integer
|
1
Min: 1 |
batch size
|
max_train_epoches |
integer
|
20
Min: 1 |
max train epoches
|
save_every_n_epochs |
integer
|
5
Min: 1 |
save every n epochs
|
train_unet_only |
boolean
|
False
|
train U-Net only
|
train_text_encoder_only |
boolean
|
False
|
train Text Encoder only
|
seed |
integer
|
98796
Min: 1 |
reproducable seed
|
noise_offset |
number
|
0
Max: 1 |
noise offset
|
keep_tokens |
integer
|
0
|
keep heading N tokens when shuffling caption tokens
|
learning_rate |
number
|
4
Min: 1 Max: 9 |
Learning rate. It means 0.0001 or 0.0009
|
unet_lr |
number
|
1
Min: 1 Max: 9 |
UNet learning rate. It means 0.0001 or 0.0009
|
text_encoder_lr |
number
|
1
Min: 1 Max: 9 |
Text Encoder learning rate. It means 0.0001 or 0.0009
|
lr_scheduler |
string
(enum)
|
cosine
Options: linear, cosine, cosine_with_restarts, polynomial, constant, constant_with_warmup |
"linear", "cosine", "cosine_with_restarts", "polynomial", "constant", "constant_with_warmup
|
lr_warmup_steps |
integer
|
0
|
warmup steps
|
lr_scheduler_num_cycles |
integer
|
1
Min: 1 |
cosine_with_restarts restart cycles
|
min_bucket_reso |
integer
|
256
Min: 1 |
arb min resolution
|
max_bucket_reso |
integer
|
1024
Min: 1 |
arb max resolution
|
persistent_data_loader_workers |
boolean
|
True
|
makes workers persistent, further reduces/eliminates the lag in between epochs. however it may increase memory usage
|
clip_skip |
integer
|
1
|
clip skip
|
optimizer_type |
string
(enum)
|
Lion
Options: adaFactor, AdamW, AdamW8bit, Lion, SGDNesterov, SGDNesterov8bit, DAdaptation, Prodigy |
adaFactor","AdamW","AdamW8bit","Lion","SGDNesterov","SGDNesterov8bit","DAdaptation", "Lion", "Prodigy
|
network_module |
string
(enum)
|
networks.lora
Options: networks.lora, networks.dylora, lycoris.kohya |
Network module
|
network_dim |
integer
|
32
Min: 1 |
network dimension
|
network_alpha |
integer
|
16
Min: 1 |
network alpha
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'format': 'uri', 'title': 'Output', 'type': 'string'}