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edenartlab /sdxl-lora-trainer:f11c84d6

Playground API

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
lora_training_urls
string
Training images for new LORA concept (can be image urls or a .zip file of images)
concept_mode
string
style
'face' / 'style' / 'object' (default)
sd_model_version
string
sdxl
'sdxl' / 'sd15'
name
string
unnamed
Name of new LORA concept
seed
integer
Random seed for reproducible training. Leave empty to use a random seed
resolution
integer
512
Square pixel resolution which your images will be resized to for training, recommended: 512 or 640
train_batch_size
integer
4
Batch size (per device) for training
max_train_steps
integer
400
Number of training steps.
token_warmup_steps
integer
0
Number of steps for token (textual_inversion) warmup.
checkpointing_steps
integer
10000
Number of steps between saving checkpoints. Set to very very high number to disable checkpointing, because you don't need intermediate checkpoints.
unet_lr
number
0.001
final learning rate of unet (after warmup)
ti_lr
number
0.001
Learning rate for training textual inversion embeddings. Don't alter unless you know what you're doing.
freeze_ti_after_completion_f
number
1
Fraction of training steps after which to freeze textual inversion embeddings
lora_rank
integer
16
Rank of LoRA embeddings for the unet.
caption_model
string
blip
Which captioning model to use. ['gpt4-v', 'blip'] are supported right now
n_tokens
integer
2
How many new tokens to inject per concept
verbose
boolean
True
verbose output
debug
boolean
False
For debugging locally only (dont activate this on replicate)

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema 
{'items': {'properties': {'attributes': {'title': 'Attributes',
                                         'type': 'object'},
                          'files': {'default': [],
                                    'items': {'format': 'uri',
                                              'type': 'string'},
                                    'title': 'Files',
                                    'type': 'array'},
                          'isFinal': {'default': False,
                                      'title': 'Isfinal',
                                      'type': 'boolean'},
                          'name': {'title': 'Name', 'type': 'string'},
                          'progress': {'title': 'Progress', 'type': 'number'},
                          'thumbnails': {'default': [],
                                         'items': {'format': 'uri',
                                                   'type': 'string'},
                                         'title': 'Thumbnails',
                                         'type': 'array'}},
           'title': 'CogOutput',
           'type': 'object'},
 'title': 'Output',
 'type': 'array',
 'x-cog-array-type': 'iterator'}