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edenartlab /sdxl-lora-trainer:503242c6
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 |
|---|---|---|---|
| name |
string
|
unnamed
|
Name of new LORA concept
|
| lora_training_urls |
string
|
Training images for new LORA concept (can be image urls or an url to a .zip file of images)
|
|
| concept_mode |
string
(enum)
|
style
Options: style, face, object |
What are you trying to learn?
|
| sd_model_version |
string
(enum)
|
sdxl
Options: sdxl, sd15 |
SDXL gives much better LoRa's if you just need static images. If you want to make AnimateDiff animations, train an SD15 lora.
|
| max_train_steps |
integer
|
400
Min: 200 Max: 1000 |
Number of training steps. Increasing this usually leads to overfitting, only viable if you have > 100 training imgs. For faces you may want to reduce to eg 300
|
| resolution |
integer
|
512
Min: 512 Max: 768 |
Square pixel resolution which your images will be resized to for training, highly recommended: 512 or 640
|
| train_batch_size |
integer
|
4
Min: 1 Max: 8 |
Batch size (per device) for training (dont increase unless running on a BIG GPU)
|
| unet_lr |
number
|
0.001
Max: 0.003 |
final learning rate of unet (after warmup), increasing this usually leads to strong overfitting
|
| ti_lr |
number
|
0.001
Max: 0.002 |
Learning rate for training textual inversion embeddings. Don't alter unless you know what you're doing.
|
| lora_rank |
integer
|
16
Min: 1 Max: 64 |
Rank of LoRA embeddings for the unet.
|
| use_dora |
boolean
|
False
|
Use Dora instead of LoRa
|
| n_tokens |
integer
|
2
Min: 1 Max: 3 |
How many new tokens to train (highly recommended to leave this at 2)
|
| seed |
integer
|
Random seed for reproducible training. Leave empty to use a random seed
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'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'}