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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 |
|---|---|---|---|
| input_images |
string
|
A zip file containing the images that will be used for training.
|
|
| instance_prompt |
string
|
a photo of TOK dog
|
Instance prompt to trigger the image generation
|
| resolution |
integer
|
1024
Min: 512 Max: 1024 |
The resolution for input images, all the images in the train/validation dataset will be resized to this
|
| train_batch_size |
integer
|
1
Min: 1 Max: 8 |
Batch size for the training dataloader
|
| gradient_accumulation_steps |
integer
|
1
Min: 1 Max: 8 |
Number of updates steps to accumulate before performing a backward/update pass
|
| learning_rate |
number
|
1
Min: 0.0001 Max: 1 |
Initial learning rate to use (1.0 for Prodigy)
|
| lr_scheduler |
None
|
constant
|
'The scheduler type to use
|
| max_train_steps |
integer
|
1000
Min: 10 Max: 6000 |
Total number of training steps to perform
|
| checkpointing_steps |
integer
|
Min: 100 Max: 6000 |
Save a checkpoint of the training state every X updates
|
| seed |
integer
|
Seed for reproducibility
|
|
| hf_token |
string
|
Huggingface token (optional) with write access to upload to Hugging Face
|
|
| hub_model_id |
string
|
Huggingface model location for upload. Requires HF token. Ex: lucataco/dreambooth-lora
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'format': 'uri', 'title': 'Output', 'type': 'string'}