---
license: openrail++
language:
- en
tags:
- coreml
- text-to-image
- stable-diffusion-xl
---
# Core ML Converted SDXL 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).
  - 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.
  - `original` version is only compatible with `CPU & GPU` option
  - `split_einsum` version takes **about 5-10 minutes** to load the model for the first time and is available for both `CPU & Neural Engine` and `CPU & GPU` options. If your Mac has a lot of GPUs, using the CPU & GPU option will speed up image generation.
  - Resolution and bit size are as noted in the individual file names.
  - This model requires macOS 14.0 or later to run properly.
  - This model was converted with a `vae-encoder` for use with `image2image`.
  - 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).
  - This model can not be used with ControlNet.

# CounterfeitXL-V2.0
Sources: [Hugging Face](https://huggingface.co./gsdf/CounterfeitXL-V2.0)
  - CoreML models are converted from CounterfeitXL-V2.5.safetensors.

The remaining contents of this model card were copied from the original CounterfeitXL-V2.0 repo

Civitai & Sample prompts  
https://civitai.com/models/118406/counterfeitxl

CounterfeitXL-V2.0 has been primarily trained on the latest illustrations but encounters a recurring issue with the appearance of halos.   
In such cases, please include 'halo' in negative prompts.  

I have incorporated style tags into some of the training images. By describing these tags in the prompt, various effects can be achieved.   
Additionally, inserting style tags into negative prompts or combining them allows for the generation of images that align with your imagined.

Style Tags  
masterpiece: Beautifully and intricately drawn illustrations.  
cinematic style: Stunning illustrations with detailed backgrounds and lighting.  
aesthetic style: Illustrations featuring beautiful color schemes.  
cute style: Cute.  
flat color: Illustrations with strong lines and a minimal color palette.  
anime style: Anime.  
comic style: Illustrations characterized by bold color choices and abstract representations.


![](https://huggingface.co./gsdf/CounterfeitXL-V2.0/resolve/main/sample.jpg)
![](https://huggingface.co./gsdf/CounterfeitXL-V2.0/resolve/main/xyz_grid.png)