# 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>
  
# Note: Some models do not have the [unet split into chunks](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).
# Note #2: "V2.5-VAE" versions have the included counterfiet v2.5 vae embedded.

# Counterfeit:
Source(s): [Hugging Face](https://huggingface.co/gsdf) - [CivitAI](https://civitai.com/models/4468/counterfeit-v25)

Counterfeit is anime style Stable Diffusion model.
DreamBooth + Merge Block Weights + Merge LoRA

# Counterfeit-V2.5 e.g. 
![sample1](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample01.png)
```
((masterpiece,best quality)),1girl, solo, animal ears, rabbit, barefoot, knees up, dress, sitting, rabbit ears, short sleeves, looking at viewer, grass, short hair, smile, white hair, puffy sleeves, outdoors, puffy short sleeves, bangs, on ground, full body, animal, white dress, sunlight, brown eyes, dappled sunlight, day, depth of field  
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 448x768, Denoising strength: 0.6, Hires upscale: 1.8, Hires upscaler: Latent
```

![sample2](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample02.png)
```
((masterpiece,best quality)),1girl, from below, solo, school uniform, serafuku, sky, cloud, black hair, skirt, sailor collar, looking at viewer, short hair, building, bangs, neckerchief, long sleeves, cloudy sky, power lines, shirt, cityscape, pleated skirt, scenery, blunt bangs, city, night, black sailor collar, closed mouth, black skirt, medium hair, school bag , holding bag  
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 832x512, Denoising strength: 0.6, Hires upscale: 1.8, Hires upscaler: Latent
```

![sample3](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample03.png)
```
((masterpiece,best quality)),2girls, black kimono, black legwear, black ribbon, black hair, cherry blossoms, day, flower, hair bun, hair ribbon, japanese clothes, kimono, long hair, looking at viewer, looking back, multiple girls, obi, outdoors, red eyes, red hair, ribbon, sandals, single hair bun, stairs, standing, statue, torii, tree, white kimono, yellow eyes   
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 640x960, Denoising strength: 0.58, Hires upscale: 1.8, Hires upscaler: Latent
```
  
![sample4](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample04.png)
```
((masterpiece,best quality)),1girl, bangs, blue eyes, blurry background, branch, brown hair, dappled sunlight, flower, from side, hair flower, hair ornament, japanese clothes, kimono, leaf, (maple leaf:1.9), obi, outdoors, sash, solo, sunlight, upper body   
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 864x512, Denoising strength: 0.58, Hires upscale: 1.8, Hires upscaler: Latent
```
  
![sample5](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample05.png)
```
((masterpiece,best quality))1girl, solo, black skirt, blue eyes, electric guitar, guitar, headphones, holding, holding plectrum, instrument, long hair, , music, one side up, pink hair, playing guiter, pleated skirt, black shirt, indoors   
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 864x512, Denoising strength: 0.58, Hires upscale: 1.8, Hires upscaler: Latent
```
  
![sample6](https://huggingface.co/gsdf/Counterfeit-V2.5/resolve/main/V2.5_sample/sample06.png)
```
((masterpiece,best quality)), 1girl, food, fruit, solo, skirt, shop, indoors, jacket, shopping, basket, jewelry, shirt, shelf, short hair, black hair, plaid skirt, black jacket, dutch angle, yellow eyes, looking at viewer   
Negative prompt: EasyNegative, extra fingers,fewer fingers,  
Steps: 20, Sampler: DPM++ 2M Karras, CFG scale: 10, Size: 864x512, Denoising strength: 0.58, Hires upscale: 1.8, Hires upscaler: Latent
```

# Counterfeit-V3.0
・I have utilized BLIP-2 as a part of the training process. Natural language prompts might be more effective.  
・I prioritize the freedom of composition, which may result in a higher possibility of anatomical errors.  
・The expressiveness has been improved by merging with negative values, but the user experience may differ from previous checkpoints.  
・I have uploaded a new Negative Embedding, trained with Counterfeit-V3.0.   
There's likely no clear superiority or inferiority between this and the previous embedding, so feel free to choose according to your preference.Note that I'm not specifically recommending the use of this embedding.  

# Sample image
prompt & Setting: https://civitai.com/models/4468/counterfeit-v30
![01](https://huggingface.co/gsdf/Counterfeit-V3.0/resolve/main/images/01.png)
![02](https://huggingface.co/gsdf/Counterfeit-V3.0/resolve/main/images/02.png)



{"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>
  
# Note: Some models do not have the unet split into chunks.
# Note #2: "V2.5-VAE" versions have the included counterfiet v2.5 vae embedded.

# Counterfeit:
Source(s): Hugging Face - CivitAI

Counterfeit is anime style Stable Diffusion model.
DreamBooth + Merge Block Weights + Merge LoRA

# Counterfeit-V2.5 e.g. 
!sample1


!sample2


!sample3

  
!sample4

  
!sample5

  
!sample6


# Counterfeit-V3.0
・I have utilized BLIP-2 as a part of the training process. Natural language prompts might be more effective.  
・I prioritize the freedom of composition, which may result in a higher possibility of anatomical errors.  
・The expressiveness has been improved by merging with negative values, but the user experience may differ from previous checkpoints.  
・I have uploaded a new Negative Embedding, trained with Counterfeit-V3.0.   
There's likely no clear superiority or inferiority between this and the previous embedding, so feel free to choose according to your preference.Note that I'm not specifically recommending the use of this embedding.  

# Sample image
prompt & Setting: URL
!01
!02



# 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> # Note: Some models do not have the unet split into chunks. # Note #2: "V2.5-VAE" versions have the included counterfiet v2.5 vae embedded. # Counterfeit:
Source(s): Hugging Face - CivitAI

Counterfeit is anime style Stable Diffusion model.
DreamBooth + Merge Block Weights + Merge LoRA # Counterfeit-V2.5 e.g. 
!sample1


!sample2


!sample3

  
!sample4

  
!sample5

  
!sample6 # Counterfeit-V3.0
・I have utilized BLIP-2 as a part of the training process. Natural language prompts might be more effective.  
・I prioritize the freedom of composition, which may result in a higher possibility of anatomical errors.  
・The expressiveness has been improved by merging with negative values, but the user experience may differ from previous checkpoints.  
・I have uploaded a new Negative Embedding, trained with Counterfeit-V3.0.   
There's likely no clear superiority or inferiority between this and the previous embedding, so feel free to choose according to your preference.Note that I'm not specifically recommending the use of this embedding. # Sample image
prompt & Setting: URL
!01
!02
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> # Note: Some models do not have the unet split into chunks. # Note #2: "V2.5-VAE" versions have the included counterfiet v2.5 vae embedded. # Counterfeit:
Source(s): Hugging Face - CivitAI

Counterfeit is anime style Stable Diffusion model.
DreamBooth + Merge Block Weights + Merge LoRA # Counterfeit-V2.5 e.g. 
!sample1


!sample2


!sample3

  
!sample4

  
!sample5

  
!sample6 # Counterfeit-V3.0
・I have utilized BLIP-2 as a part of the training process. Natural language prompts might be more effective.  
・I prioritize the freedom of composition, which may result in a higher possibility of anatomical errors.  
・The expressiveness has been improved by merging with negative values, but the user experience may differ from previous checkpoints.  
・I have uploaded a new Negative Embedding, trained with Counterfeit-V3.0.   
There's likely no clear superiority or inferiority between this and the previous embedding, so feel free to choose according to your preference.Note that I'm not specifically recommending the use of this embedding. # Sample image
prompt & Setting: URL
!01
!02
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># Note: Some models do not have the unet split into chunks.# Note #2: "V2.5-VAE" versions have the included counterfiet v2.5 vae embedded.# Counterfeit:
Source(s): Hugging Face - CivitAI

Counterfeit is anime style Stable Diffusion model.
DreamBooth + Merge Block Weights + Merge LoRA# Counterfeit-V2.5 e.g. 
!sample1


!sample2


!sample3

  
!sample4

  
!sample5

  
!sample6# Counterfeit-V3.0
・I have utilized BLIP-2 as a part of the training process. Natural language prompts might be more effective.  
・I prioritize the freedom of composition, which may result in a higher possibility of anatomical errors.  
・The expressiveness has been improved by merging with negative values, but the user experience may differ from previous checkpoints.  
・I have uploaded a new Negative Embedding, trained with Counterfeit-V3.0.   
There's likely no clear superiority or inferiority between this and the previous embedding, so feel free to choose according to your preference.Note that I'm not specifically recommending the use of this embedding.# Sample image
prompt & Setting: URL
!01
!02