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dreambooth-piranesi
keras-dreambooth/dreambooth-piranesi
dreambooth-piranesi 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 keras. The card lists the license as apache-2.0.
This is a Keras Dreambooth model fine-tuned to some 18th century etching artworks by italian artist Giambattista Piranesi.
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At a glance
- Task
- Text-to-Image
- Library
- keras
- License
- apache-2.0
- Access
- Public
- Created
- Mar 23, 2023
- Updated
- Mar 24, 2023
- SHA
- 9926dcdc
Model card
From the Hugging Face model README
Model description
This is a Keras Dreambooth model fine-tuned to some 18th century etching artworks by italian artist Giambattista Piranesi.
A few samples below
Intended uses & limitations
The base prompt is "image of monuments in sks style". A slightly better prompt would be "image of monuments in sks style, 8k, high quality, old paper" with negative prompt "distorted".
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 |
- Task
- Text-to-Image
- Library
- keras
- License
- apache-2.0
- Created
- Mar 23, 2023
- Updated
- Mar 24, 2023