
## 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 |
{"license": "cc-by-nc-4.0", "library_name": "keras", "tags": ["keras-dreambooth", "scifi"]}
keras keras-dreambooth scifi license:cc-by-nc-4.0 region:us
TAGS
#keras #keras-dreambooth #scifi #license-cc-by-nc-4.0 #region-us 

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
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager


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 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 were used for training.


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:




### 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
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager


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 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 were used for training.


Training procedure
------------------ ### Training hyperparameters


The following hyperparameters were used during training:
TAGS
#keras #keras-dreambooth #scifi #license-cc-by-nc-4.0 #region-us 
 ### 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
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager


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 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 were used for training.


Training procedure
------------------ ### Training hyperparameters


The following hyperparameters were used during training:
TAGS
#keras #keras-dreambooth #scifi #license-cc-by-nc-4.0 #region-us 
### 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
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager
!Sample Image of the Voyager


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 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 were used for training.


Training procedure
------------------### Training hyperparameters


The following hyperparameters were used during training: