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dreambooth_eighties_cars

Keras
TF-Keras
keras-dreambooth
wildcard
Model card Files Community
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dreambooth_eighties_cars
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---
library_name: keras
tags:
- keras-dreambooth
- wildcard
license: cc-by-nc-4.0
---
## Model description

This Stable-Diffusion Model has been fine-tuned on images of Cars from Start to End of the 1980s.

Here are some examples using the following Hyperparameters:

Prompt: photo of eighties_cars car, high quality, 8k

Negative Prompt: bad, ugly, malformed, deformed, out of frame, blurry, cropped, noisy

Denoising Steps: 50

Guidance Scale: 7.5

![Example Image](examples/tmpy00t8dcv.png)
![Example Image](examples/tmpl2opz8ge.png)
![Example Image](examples/tmpfz8hgvyf.png)
![Example Image](examples/tmpemqvra3_.png)
![Example Image](examples/tmp870efxa6.png)
![Example Image](examples/tmp4zcmco8b.png)
![Example Image](examples/tmp4mg3h4sq.png)
![Example Image](examples/tmp3nd374rn.png)

## Intended uses & limitations

Anyone may use this model for non-commercial usecases under the Linked License, as long as Paragraph 5 of the [Open RAIL-M License](https://raw.githubusercontent.com/CompVis/stable-diffusion/main/LICENSE) are respected as well. The original Model adheres under Open RAIL-M.

It was made solely as an experiment for keras_cv Dreambooth Training.

## Training and evaluation data

More information needed

## 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 |