Downloads · 30 days
24
5% of all-time downloads
keras-dreambooth/ignatius
ignatius is a text-to-image model from keras-dreambooth. Use it when you need an image from a text prompt. It is set up for tf-keras. The card lists the license as creativeml-openrail-m.
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, e…
Downloads · 30 days
24
5% of all-time downloads
All-time downloads
531
Public
Repo size
3.5 GB
Likes
2
Public
Click a slice to open those files.
.data-00000-of-000013.4 GB · 99%
From the Hugging Face model README
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.

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.
To train this model, this was the training notebook and the trainig dataset was this one
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 |

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