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zenaivn /dreambooth-training:103a77cb
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 |
---|---|---|---|
gender |
string
|
Specify the gender (for example: man/woman).
|
|
identifier |
string
|
ohwx
|
Unique identifier for the model instance.
|
num_repeats |
string
|
1
|
Number of times the input images should be repeated.
|
output_name |
string
|
Name of the model's output file. (for example: output_model)
|
|
instance_data |
string
|
A ZIP file containing your training images (JPG, PNG, etc. size not restricted). These images contain your 'subject' that you want the trained model to embed in the output domain for later generating customized scenes beyond the training images. For best results, use images without noise or unrelated objects in the background.
|
|
class_data |
string
|
An optional ZIP file containing the training data of class images. This corresponds to `class_prompt` above, also with the purpose of keeping the model generalizable. By default, the pretrained stable-diffusion model will generate N images (determined by the `num_class_images` you set) based on the `class_prompt` provided. But to save time or to have your preferred specific set of `class_data`, you can also provide them in a ZIP file.
|
|
train_batch_size |
integer
|
2
|
Batch size for training data loader, applied per device.
|
max_train_steps |
integer
|
Total number of training steps to perform. It should be number of input images * 100. For example, 14 images * 100 = 1400 steps)
|
|
learning_rate |
number
|
0.000001
|
Initial learning rate (after the potential warmup period) to use.
|
learning_rate_te |
number
|
0.000001
|
Initial learning rate te (after the potential warmup period) to use.
|
lr_scheduler |
None
|
cosine
|
The scheduler type to use
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}