# 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.<br>
  - `original` version is only compatible with CPU & GPU option.<br>
  - Custom resolution versions are tagged accordingly.<br>
  - `vae` tagged files have a vae embedded into the model.<br>
  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
  - This model was converted with `vae-encoder` for i2i.
  - Models that are 32 bit will have "fp32" in the filename.
  
# Note: Some models do not have the [unet split into chunks](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).

# SNVHS:
Source(s): [CivitAI](https://civitai.com/models/15057/snvhsv1)

Model trained on liminal space pictures I took after applying a simple VHS filter on it, using https://civitai.com/models/13941/epinoiseoffset in combination with this model works well!
{"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.<br>
  - 'original' version is only compatible with CPU & GPU option.<br>
  - Custom resolution versions are tagged accordingly.<br>
  - 'vae' tagged files have a vae embedded into the model.<br>
  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
  - This model was converted with 'vae-encoder' for i2i.
  - Models that are 32 bit will have "fp32" in the filename.
  
# Note: Some models do not have the unet split into chunks.

# SNVHS:
Source(s): CivitAI

Model trained on liminal space pictures I took after applying a simple VHS filter on it, using URL in combination with this model works well!
# 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.<br>
  - 'original' version is only compatible with CPU & GPU option.<br>
  - Custom resolution versions are tagged accordingly.<br>
  - 'vae' tagged files have a vae embedded into the model.<br>
  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
  - This model was converted with 'vae-encoder' for i2i.
  - Models that are 32 bit will have "fp32" in the filename. # Note: Some models do not have the unet split into chunks. # SNVHS:
Source(s): CivitAI

Model trained on liminal space pictures I took after applying a simple VHS filter on it, using URL in combination with this model works well!
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.<br>
  - 'original' version is only compatible with CPU & GPU option.<br>
  - Custom resolution versions are tagged accordingly.<br>
  - 'vae' tagged files have a vae embedded into the model.<br>
  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
  - This model was converted with 'vae-encoder' for i2i.
  - Models that are 32 bit will have "fp32" in the filename. # Note: Some models do not have the unet split into chunks. # SNVHS:
Source(s): CivitAI

Model trained on liminal space pictures I took after applying a simple VHS filter on it, using URL in combination with this model works well!
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.<br>
  - 'original' version is only compatible with CPU & GPU option.<br>
  - Custom resolution versions are tagged accordingly.<br>
  - 'vae' tagged files have a vae embedded into the model.<br>
  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
  - This model was converted with 'vae-encoder' for i2i.
  - Models that are 32 bit will have "fp32" in the filename.# Note: Some models do not have the unet split into chunks.# SNVHS:
Source(s): CivitAI

Model trained on liminal space pictures I took after applying a simple VHS filter on it, using URL in combination with this model works well!