README.md

---
language:
- en
library_name: tf-keras
license: creativeml-openrail-m
tags:
- stable-diffusion
- text-to-image
- keras-dreambooth
- wild-card
inference: true
---

## Model description

The Ignatius Farray dreambooth model would be a sleek and modern diffusion model designed to transport users into a world of absurdity and hilarity. 
I cannot promise that all the images would be adorned with bright, eye-catching colors and images that reflect Ignatius' unique sense of style and humor.

## Images generated by model

![summary_image](./ignatius_summary.png)

## Intended uses & limitations

You can use to create images based on Ignatius and put him in different situations. Try not to use for bad purpose and use the "commedia" on it.

## Training and evaluation data

To train this model, this was the training [notebook](https://colab.research.google.com/github/huggingface/community-events/blob/main/keras-dreambooth-sprint/Dreambooth_on_Hub.ipynb) and the trainig dataset was this [one](https://huggingface.co/datasets/matallanas/ignatius)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:

| Hyperparameters | Value |
| :-- | :-- |
| inner_optimizer.class_name | Custom>RMSprop |
| inner_optimizer.config.name | RMSprop |
| inner_optimizer.config.weight_decay | None |
| inner_optimizer.config.clipnorm | None |
| inner_optimizer.config.global_clipnorm | None |
| inner_optimizer.config.clipvalue | None |
| inner_optimizer.config.use_ema | False |
| inner_optimizer.config.ema_momentum | 0.99 |
| inner_optimizer.config.ema_overwrite_frequency | 100 |
| inner_optimizer.config.jit_compile | True |
| inner_optimizer.config.is_legacy_optimizer | False |
| inner_optimizer.config.learning_rate | 0.0010000000474974513 |
| inner_optimizer.config.rho | 0.9 |
| inner_optimizer.config.momentum | 0.0 |
| inner_optimizer.config.epsilon | 1e-07 |
| inner_optimizer.config.centered | False |
| dynamic | True |
| initial_scale | 32768.0 |
| dynamic_growth_steps | 2000 |
| training_precision | mixed_float16 |


 ## Model Plot

<details>
<summary>View Model Plot</summary>

![Model Image](./model.png)

</details>

## Usage

The instance token used is "ignatius". A prompt example is as follows "a photo of ignatius on a car"

```python
from huggingface_hub import from_pretrained_keras
import keras_cv

sd_dreambooth_model = keras_cv.models.StableDiffusion(
    img_width=resolution, img_height=resolution, jit_compile=True, 
)
loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/ignatius")
sd_dreambooth_model._diffusion_model = loaded_diffusion_model

prompt = f"ignatius on the moon"

#generated_img = sd_dreambooth_model.text_to_image(
generated_img = dreambooth_model.text_to_image(
    prompt,
    batch_size=4,
    num_steps=150,
    unconditional_guidance_scale=15,
)
```