
## Model description

This model is a fine-tuned Stable Diffusion modeled, using the Dreambooth technique.
It was trained on 43 screenshots of the game Return To Monkey Island, scraped from the Internet. You can find the full set here: [Return To Monkey Island Screenshots](https://huggingface.co/datasets/keras-dreambooth/monkey_island_screenshots)

The result resembles the style from the game, even though you should not expect wonders and rather see it as its own style inspired by the game's.

It was created by [johko](https://huggingface.co/johko) for the [keras-dreambooth](https://huggingface.co/keras-dreambooth) sprint.

## Training procedure

This model was trained using the keras implementation of dreambooth. 
You can find the notebook to train these models and how to attend this sprint [here](https://github.com/huggingface/community-events/tree/main/keras-dreambooth-sprint).


## Example Outputs

Geralt of Rivia
![Geralt of Rivia in Monkey Island Style](mnky_geralt.png) 

Frodo Baggins
![Frodo Baggins in Monkey Island Style](mnky_frodo.png) 

Han Solo
![Han Solo in Monkey Island Style](mnky_han.png) 



### 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 |


 ## Model Plot

<details>
<summary>View Model Plot</summary>

![Model Image](./model.png)

</details>
{"license": "apache-2.0", "library_name": "keras", "tags": ["keras-dreambooth"], "pipeline_tag": "text-to-image"}
keras keras-dreambooth text-to-image license:apache-2.0 has_space region:us
TAGS
#keras #keras-dreambooth #text-to-image #license-apache-2.0 #has_space #region-us 

Model description
-----------------


This model is a fine-tuned Stable Diffusion modeled, using the Dreambooth technique.
It was trained on 43 screenshots of the game Return To Monkey Island, scraped from the Internet. You can find the full set here: Return To Monkey Island Screenshots


The result resembles the style from the game, even though you should not expect wonders and rather see it as its own style inspired by the game's.


It was created by johko for the keras-dreambooth sprint.


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


This model was trained using the keras implementation of dreambooth.
You can find the notebook to train these models and how to attend this sprint here.


Example Outputs
---------------


Geralt of Rivia
!Geralt of Rivia in Monkey Island Style


Frodo Baggins
!Frodo Baggins in Monkey Island Style


Han Solo
!Han Solo in Monkey Island Style


### Training hyperparameters


The following hyperparameters were used during training:



Model Plot
----------



View Model Plot
!Model Image



### Training hyperparameters


The following hyperparameters were used during training:



Model Plot
----------



View Model Plot
!Model Image
TAGS
#keras #keras-dreambooth #text-to-image #license-apache-2.0 #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:



Model Plot
----------



View Model Plot
!Model Image
TAGS
#keras #keras-dreambooth #text-to-image #license-apache-2.0 #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:



Model Plot
----------



View Model Plot
!Model Image