---
library_name: keras
tags:
- keras-dreambooth
- scifi
license: cc-by-nc-4.0
---

## Model description

This Stable-Diffusion Model has been fine-tuned on images of the Star Trek Voyager Spaceship.

### Here are some examples that were created using the model using these settings:

Prompt: photo of voyager spaceship in space, high quality, blender, 3d, trending on artstation, 8k

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

Denoising Steps: 50

![Sample Image of the Voyager](./samples/tmp4r3restm.png)
![Sample Image of the Voyager](./samples/tmp_6_ybon8.png)
![Sample Image of the Voyager](./samples/tmpew9t_8ni.png)
![Sample Image of the Voyager](./samples/tmpnjp83zql.png)
![Sample Image of the Voyager](./samples/tmppvqhu8rb.png)
![Sample Image of the Voyager](./samples/tmpxb8rwlo0.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.

Since a lot of orthographic views were used, the model seems to be biased around them, and has issues creating more variance and poses. While inferring, the background appears noisy. 

## Training and evaluation data

Images from Rob Bonchune from [Trekcore](https://blog.trekcore.com/) were used for training.

## 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 |