README.md

---
library_name: tf-keras
license: creativeml-openrail-m
tags:
- keras-cv
- diffusers
- stable-diffusion
- text-to-image
- diffusion-models-class
- dreambooth
- nature
widget:
- text: a photo of puggieace dog on the beach
---

# 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](https://huggingface.co/keras-dreambooth) 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

```python
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 |