# Core ML Converted Model:

  - This model was converted to [Core ML for use on Apple Silicon devices](https://github.com/apple/ml-stable-diffusion). Conversion instructions can be found [here](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-ckpt-or-safetensors-files-to-Core-ML).<br>
  - Provide the model to an app such as **Mochi Diffusion** [Github](https://github.com/godly-devotion/MochiDiffusion) - [Discord](https://discord.gg/x2kartzxGv) to generate images.<br>
  - `split_einsum` version is compatible with all compute unit options including Neural Engine.
  - `original` version is only compatible with `CPU & GPU` option.
  - Custom resolution versions are tagged accordingly.
  - The `vae-ft-mse-840000-ema-pruned.ckpt` vae is embedded into the model.
  - This model was converted with a `vae-encoder` for `image2image`.
  - This model is `fp16`.
  - Descriptions are posted as-is from original model source.
  - Not all features and/or results may be available in CoreML format.
  - This model does not have the [unet split into chunks](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).
  - This model does not include a safety checker (for NSFW content).

# floralPatterns-v10:
Source(s): [Hugging Face](https://huggingface.co/Mobius-labs/floral_pattern) - [CivitAI](https://civitai.com/models/26295/floral-patterns)

This model was trained to generate floral patterns.

Join our [Discord](https://discord.gg/qM84dzKC) for any questions or feedback!

**Prompting**

Use the word **"pattern"** to trigger the style. You can also use negative prompt to get rid of unwanted colors if the positive prompt isn't providing enough control.

Example prompts

    A yellow and pink pattern with flowers on white background

    A yellow and pink pattern with birds and flowers on white background

    A black and white pattern of butterflies in a jungle

The example images were all generated with fairly simple prompts, but feel free to experiment with more complex prompts as well as negative prompts.

**Settings**

Resolution must be **768 x 768** for best results

Sample images were generated with CFG = 11 and 75 inference steps. 

Inference settings otherwise shouldn’t matter too much.

![image](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/a04a8d31-f055-40f6-d152-af2811715700/width=400/358250)

![image](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/3d669764-52ec-411f-5f8a-9252f3e83900/width=400/358288)

![image](https://imagecache.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/549c6d86-5576-4d67-6eca-5c6cc4106b00/width=400/358251)
{"license": "creativeml-openrail-m", "tags": ["coreml", "stable-diffusion", "text-to-image"]}
coreml stable-diffusion text-to-image license:creativeml-openrail-m region:us
TAGS
#coreml #stable-diffusion #text-to-image #license-creativeml-openrail-m #region-us 

# Core ML Converted Model:

  - This model was converted to Core ML for use on Apple Silicon devices. Conversion instructions can be found here.<br>
  - Provide the model to an app such as Mochi Diffusion Github - Discord to generate images.<br>
  - 'split_einsum' version is compatible with all compute unit options including Neural Engine.
  - 'original' version is only compatible with 'CPU & GPU' option.
  - Custom resolution versions are tagged accordingly.
  - The 'URL' vae is embedded into the model.
  - This model was converted with a 'vae-encoder' for 'image2image'.
  - This model is 'fp16'.
  - Descriptions are posted as-is from original model source.
  - Not all features and/or results may be available in CoreML format.
  - This model does not have the unet split into chunks.
  - This model does not include a safety checker (for NSFW content).

# floralPatterns-v10:
Source(s): Hugging Face - CivitAI

This model was trained to generate floral patterns.

Join our Discord for any questions or feedback!

Prompting

Use the word "pattern" to trigger the style. You can also use negative prompt to get rid of unwanted colors if the positive prompt isn't providing enough control.

Example prompts

    A yellow and pink pattern with flowers on white background

    A yellow and pink pattern with birds and flowers on white background

    A black and white pattern of butterflies in a jungle

The example images were all generated with fairly simple prompts, but feel free to experiment with more complex prompts as well as negative prompts.

Settings

Resolution must be 768 x 768 for best results

Sample images were generated with CFG = 11 and 75 inference steps. 

Inference settings otherwise shouldn’t matter too much.

!image

!image

!image
# Core ML Converted Model:

  - This model was converted to Core ML for use on Apple Silicon devices. Conversion instructions can be found here.<br>
  - Provide the model to an app such as Mochi Diffusion Github - Discord to generate images.<br>
  - 'split_einsum' version is compatible with all compute unit options including Neural Engine.
  - 'original' version is only compatible with 'CPU & GPU' option.
  - Custom resolution versions are tagged accordingly.
  - The 'URL' vae is embedded into the model.
  - This model was converted with a 'vae-encoder' for 'image2image'.
  - This model is 'fp16'.
  - Descriptions are posted as-is from original model source.
  - Not all features and/or results may be available in CoreML format.
  - This model does not have the unet split into chunks.
  - This model does not include a safety checker (for NSFW content). # floralPatterns-v10:
Source(s): Hugging Face - CivitAI

This model was trained to generate floral patterns.

Join our Discord for any questions or feedback!

Prompting

Use the word "pattern" to trigger the style. You can also use negative prompt to get rid of unwanted colors if the positive prompt isn't providing enough control.

Example prompts

    A yellow and pink pattern with flowers on white background

    A yellow and pink pattern with birds and flowers on white background

    A black and white pattern of butterflies in a jungle

The example images were all generated with fairly simple prompts, but feel free to experiment with more complex prompts as well as negative prompts.

Settings

Resolution must be 768 x 768 for best results

Sample images were generated with CFG = 11 and 75 inference steps. 

Inference settings otherwise shouldn’t matter too much.

!image

!image

!image
TAGS
#coreml #stable-diffusion #text-to-image #license-creativeml-openrail-m #region-us 
 # Core ML Converted Model:

  - This model was converted to Core ML for use on Apple Silicon devices. Conversion instructions can be found here.<br>
  - Provide the model to an app such as Mochi Diffusion Github - Discord to generate images.<br>
  - 'split_einsum' version is compatible with all compute unit options including Neural Engine.
  - 'original' version is only compatible with 'CPU & GPU' option.
  - Custom resolution versions are tagged accordingly.
  - The 'URL' vae is embedded into the model.
  - This model was converted with a 'vae-encoder' for 'image2image'.
  - This model is 'fp16'.
  - Descriptions are posted as-is from original model source.
  - Not all features and/or results may be available in CoreML format.
  - This model does not have the unet split into chunks.
  - This model does not include a safety checker (for NSFW content). # floralPatterns-v10:
Source(s): Hugging Face - CivitAI

This model was trained to generate floral patterns.

Join our Discord for any questions or feedback!

Prompting

Use the word "pattern" to trigger the style. You can also use negative prompt to get rid of unwanted colors if the positive prompt isn't providing enough control.

Example prompts

    A yellow and pink pattern with flowers on white background

    A yellow and pink pattern with birds and flowers on white background

    A black and white pattern of butterflies in a jungle

The example images were all generated with fairly simple prompts, but feel free to experiment with more complex prompts as well as negative prompts.

Settings

Resolution must be 768 x 768 for best results

Sample images were generated with CFG = 11 and 75 inference steps. 

Inference settings otherwise shouldn’t matter too much.

!image

!image

!image
TAGS
#coreml #stable-diffusion #text-to-image #license-creativeml-openrail-m #region-us 
# Core ML Converted Model:

  - This model was converted to Core ML for use on Apple Silicon devices. Conversion instructions can be found here.<br>
  - Provide the model to an app such as Mochi Diffusion Github - Discord to generate images.<br>
  - 'split_einsum' version is compatible with all compute unit options including Neural Engine.
  - 'original' version is only compatible with 'CPU & GPU' option.
  - Custom resolution versions are tagged accordingly.
  - The 'URL' vae is embedded into the model.
  - This model was converted with a 'vae-encoder' for 'image2image'.
  - This model is 'fp16'.
  - Descriptions are posted as-is from original model source.
  - Not all features and/or results may be available in CoreML format.
  - This model does not have the unet split into chunks.
  - This model does not include a safety checker (for NSFW content).# floralPatterns-v10:
Source(s): Hugging Face - CivitAI

This model was trained to generate floral patterns.

Join our Discord for any questions or feedback!

Prompting

Use the word "pattern" to trigger the style. You can also use negative prompt to get rid of unwanted colors if the positive prompt isn't providing enough control.

Example prompts

    A yellow and pink pattern with flowers on white background

    A yellow and pink pattern with birds and flowers on white background

    A black and white pattern of butterflies in a jungle

The example images were all generated with fairly simple prompts, but feel free to experiment with more complex prompts as well as negative prompts.

Settings

Resolution must be 768 x 768 for best results

Sample images were generated with CFG = 11 and 75 inference steps. 

Inference settings otherwise shouldn’t matter too much.

!image

!image

!image