Before you start you will need a deepctl command line tool.
Dreambooth is a fine-tuning technique that lets Stable Diffusion mimic patterns provided in the subject's instance data. You will need an archive containing 10-20 images of an instance. We recommend resizing images to 512x512, resolution which Stable Diffusion 1.5 was trained in. For instance prompt you can use 3 letter sequence (e.g. "nkb"). For max_train_steps we recommend something between 800 and 2000. You have to pass output_model_name, to use later for inference on your fine-tuned model.
deepctl infer -m 'deepinfra/dreambooth'\ -i 'instance_prompt=["a photo of nkb person"]'\ -i 'class_prompt=["a photo of a person"]'\ -i instance_data=@/path/to/instance_data.zip\ -i max_train_steps=800\ -i output_model_name=your_github_username/your_custom_model_name -i webhook=https://example.com/webhook
Make sure your model name starts with your Github username before '/'. The result will be delivered in a webhook or in a response if you haven't provided one.
You can use it with either our rest API or our deepctl command line. Here is how to use it with the command line tool:
deepctl infer -m your_github_username/your_custom_model_name\ -i prompt="a colorful painting of zwt person"\ -o images=zwt_gta5.png
To see the full documentation of how to call this model checkout out the documentation page:
deepctl model info -m your_github_username/your_custom_model_name
If you have any question, just reach out to us on our Discord server.