# 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).

# Vintedois (22h) Diffusion:
Source(s): [Hugging Face](https://huggingface.co/22h/vintedois-diffusion-v0-1) - [CivitAI](https://civitai.com/models/2781/vintedois-diffusion-v0-1)

### Vintedois (22h) Diffusion model trained by [Predogl](https://twitter.com/Predogl) and [piEsposito](https://twitter.com/piesposi_to) with open weights, configs and prompts (as it should be)

This model was trained on a large amount of high quality images with simple prompts to generate beautiful images without a lot of prompt engineering.

You can enforce style by prepending your prompt with `estilovintedois` if it is not good enough.

It should also be very dreamboothable, being able to generate high fidelity faces with a little amount of steps.

**You can use this model commercially or whatever, but we are not liable if you do messed up stuff with it.**

### Gradio

We support a [Gradio](https://github.com/gradio-app/gradio) Web UI to run vintedois-diffusion-v0-1 :
[![Open In Spaces](https://camo.githubusercontent.com/00380c35e60d6b04be65d3d94a58332be5cc93779f630bcdfc18ab9a3a7d3388/68747470733a2f2f696d672e736869656c64732e696f2f62616467652f25463025394625413425393725323048756767696e67253230466163652d5370616365732d626c7565)](https://huggingface.co/spaces/22h/vintedois-diffusion-v0-1)


### Model card

Everything from [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5), plus the fact that this is being built by two indie devs, so it was not extensively tested for new biases.

You can run this concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb)

### Sample results

<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/joined.png" width=1024/>

### Example prompts

- Prompt: photo of an old man in a jungle, looking at the camera
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 30
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-photo%20of%20an%20old%20man%20in%20a%20jungle%2C%20looking%20at%C2%A0the%C2%A0camera.png" width=512/>

- Prompt: kneeling cat knight, portrait, finely detailed armor, intricate design, silver, silk, cinematic lighting, 4k
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 50
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-kneeling%20cat%20knight%2C%20portrait%2C%20finely%20detailed%20armor%2C%20intricate%20design%2C%20silver%2C%20silk%2C%20cinematic%20lighting%2C%204k.png" width=512/>


- Prompt: a beautiful girl In front of the cabin, the country, by Artgerm Lau and Krenz Cushart，hyperdetailed, trending on artstation, trending on deviantart
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 50
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-a%20beautiful%20girl%20In%20front%20of%20the%20cabin%2C%20the%20country%2C%20by%20Artgerm%20Lau%20and%20Krenz%20Cushart%EF%BC%8Chyperdetailed%2C%20trending%20on%20artstation%2C%20tre.png" width=512/>

- Prompt: destroyed city
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 50
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-destroyed%20city.png" width=512/>

- Prompt: victorian city landscape
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 50
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-victorian%20city%20landscape.png" width=512/>

- Prompt: prehistoric native living room
- CFG Scale: 7.5
- Scheduler: `diffusers.EulerAncestralDiscreteScheduler`
- Steps: 50
- Seed: 44
<img src="https://huggingface.co/22h/vintedois-diffusion-v0-1/resolve/main/44-euler-a-prehistoric%20native%20living%20room.png" width=512/>

Thanks for the Google Developer Expert program for providing us with a GCP credits grant.
{"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.

# Vintedois (22h) Diffusion:
Source(s): Hugging Face - CivitAI

### Vintedois (22h) Diffusion model trained by Predogl and piEsposito with open weights, configs and prompts (as it should be)

This model was trained on a large amount of high quality images with simple prompts to generate beautiful images without a lot of prompt engineering.

You can enforce style by prepending your prompt with 'estilovintedois' if it is not good enough.

It should also be very dreamboothable, being able to generate high fidelity faces with a little amount of steps.

You can use this model commercially or whatever, but we are not liable if you do messed up stuff with it.

### Gradio

We support a Gradio Web UI to run vintedois-diffusion-v0-1 :
![Open In Spaces](URL


### Model card

Everything from Stable Diffusion v1-5, plus the fact that this is being built by two indie devs, so it was not extensively tested for new biases.

You can run this concept via 'diffusers' Colab Notebook for Inference

### Sample results

<img src="URL width=1024/>

### Example prompts

- Prompt: photo of an old man in a jungle, looking at the camera
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 30
- Seed: 44
<img src="URL width=512/>

- Prompt: kneeling cat knight, portrait, finely detailed armor, intricate design, silver, silk, cinematic lighting, 4k
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>


- Prompt: a beautiful girl In front of the cabin, the country, by Artgerm Lau and Krenz Cushart，hyperdetailed, trending on artstation, trending on deviantart
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: destroyed city
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: victorian city landscape
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: prehistoric native living room
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

Thanks for the Google Developer Expert program for providing us with a GCP credits grant.
# 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. # Vintedois (22h) Diffusion:
Source(s): Hugging Face - CivitAI ### Vintedois (22h) Diffusion model trained by Predogl and piEsposito with open weights, configs and prompts (as it should be)

This model was trained on a large amount of high quality images with simple prompts to generate beautiful images without a lot of prompt engineering.

You can enforce style by prepending your prompt with 'estilovintedois' if it is not good enough.

It should also be very dreamboothable, being able to generate high fidelity faces with a little amount of steps.

You can use this model commercially or whatever, but we are not liable if you do messed up stuff with it. ### Gradio

We support a Gradio Web UI to run vintedois-diffusion-v0-1 :
![Open In Spaces](URL ### Model card

Everything from Stable Diffusion v1-5, plus the fact that this is being built by two indie devs, so it was not extensively tested for new biases.

You can run this concept via 'diffusers' Colab Notebook for Inference ### Sample results

<img src="URL width=1024/> ### Example prompts

- Prompt: photo of an old man in a jungle, looking at the camera
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 30
- Seed: 44
<img src="URL width=512/>

- Prompt: kneeling cat knight, portrait, finely detailed armor, intricate design, silver, silk, cinematic lighting, 4k
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>


- Prompt: a beautiful girl In front of the cabin, the country, by Artgerm Lau and Krenz Cushart，hyperdetailed, trending on artstation, trending on deviantart
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: destroyed city
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: victorian city landscape
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: prehistoric native living room
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

Thanks for the Google Developer Expert program for providing us with a GCP credits grant.
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. # Vintedois (22h) Diffusion:
Source(s): Hugging Face - CivitAI ### Vintedois (22h) Diffusion model trained by Predogl and piEsposito with open weights, configs and prompts (as it should be)

This model was trained on a large amount of high quality images with simple prompts to generate beautiful images without a lot of prompt engineering.

You can enforce style by prepending your prompt with 'estilovintedois' if it is not good enough.

It should also be very dreamboothable, being able to generate high fidelity faces with a little amount of steps.

You can use this model commercially or whatever, but we are not liable if you do messed up stuff with it. ### Gradio

We support a Gradio Web UI to run vintedois-diffusion-v0-1 :
![Open In Spaces](URL ### Model card

Everything from Stable Diffusion v1-5, plus the fact that this is being built by two indie devs, so it was not extensively tested for new biases.

You can run this concept via 'diffusers' Colab Notebook for Inference ### Sample results

<img src="URL width=1024/> ### Example prompts

- Prompt: photo of an old man in a jungle, looking at the camera
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 30
- Seed: 44
<img src="URL width=512/>

- Prompt: kneeling cat knight, portrait, finely detailed armor, intricate design, silver, silk, cinematic lighting, 4k
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>


- Prompt: a beautiful girl In front of the cabin, the country, by Artgerm Lau and Krenz Cushart，hyperdetailed, trending on artstation, trending on deviantart
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: destroyed city
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: victorian city landscape
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: prehistoric native living room
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

Thanks for the Google Developer Expert program for providing us with a GCP credits grant.
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.# Vintedois (22h) Diffusion:
Source(s): Hugging Face - CivitAI### Vintedois (22h) Diffusion model trained by Predogl and piEsposito with open weights, configs and prompts (as it should be)

This model was trained on a large amount of high quality images with simple prompts to generate beautiful images without a lot of prompt engineering.

You can enforce style by prepending your prompt with 'estilovintedois' if it is not good enough.

It should also be very dreamboothable, being able to generate high fidelity faces with a little amount of steps.

You can use this model commercially or whatever, but we are not liable if you do messed up stuff with it.### Gradio

We support a Gradio Web UI to run vintedois-diffusion-v0-1 :
![Open In Spaces](URL### Model card

Everything from Stable Diffusion v1-5, plus the fact that this is being built by two indie devs, so it was not extensively tested for new biases.

You can run this concept via 'diffusers' Colab Notebook for Inference### Sample results

<img src="URL width=1024/>### Example prompts

- Prompt: photo of an old man in a jungle, looking at the camera
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 30
- Seed: 44
<img src="URL width=512/>

- Prompt: kneeling cat knight, portrait, finely detailed armor, intricate design, silver, silk, cinematic lighting, 4k
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>


- Prompt: a beautiful girl In front of the cabin, the country, by Artgerm Lau and Krenz Cushart，hyperdetailed, trending on artstation, trending on deviantart
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: destroyed city
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: victorian city landscape
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

- Prompt: prehistoric native living room
- CFG Scale: 7.5
- Scheduler: 'diffusers.EulerAncestralDiscreteScheduler'
- Steps: 50
- Seed: 44
<img src="URL width=512/>

Thanks for the Google Developer Expert program for providing us with a GCP credits grant.