nielsgl/dreambooth-pug-ace-sd2.1

DreamBooth model for the puggieace concept trained by nielsgl on the nielsgl/dreambooth-ace dataset.

This is a KerasCV Stable Diffusion V2.1 model fine-tuned on the puggieace concept with DreamBooth. It can be used by modifying the instance_prompt: a photo of puggieace

This model was created as part of the Keras DreamBooth Sprint 🔥. Visit the organisation page for instructions on how to take part!

Description

This is a KerasCV Stable Diffusion model fine-tuned on dog images for the nature theme.

Usage

from huggingface_hub import from_pretrained_keras
import keras_cv
import matplotlib.pyplot as plt


model = keras_cv.models.StableDiffusionV2(img_width=512, img_height=512, jit_compile=True)
model._diffusion_model = from_pretrained_keras(nielsgl/dreambooth-pug-ace-sd2.1)
model._text_encoder = from_pretrained_keras(nielsgl/dreambooth-pug-ace-sd2.1-text-encoder)

images = model.text_to_image("a photo of puggieace dog on the beach", batch_size=3)
plt.imshow(image[0])

Training hyperparameters

The following hyperparameters were used during training:

Hyperparameters	Value
name	RMSprop
weight_decay	None
clipnorm	None
global_clipnorm	None
clipvalue	None
use_ema	False
ema_momentum	0.99
ema_overwrite_frequency	100
jit_compile	True
is_legacy_optimizer	False
learning_rate	0.0010000000474974513
rho	0.9
momentum	0.0
epsilon	1e-07
centered	False
training_precision	float32