| --- |
| license: creativeml-openrail-m |
| thumbnail: "https://huggingface.co/coreml/coreml-anything-v3-1/resolve/main/example-images/thumbnail.png" |
| language: |
| - en |
| tags: |
| - coreml |
| - stable-diffusion |
| - stable-diffusion-diffusers |
| --- |
| |
| # Core ML Converted Model |
|
|
| This model was converted to Core ML for use on Apple Silicon devices by following Apple's instructions [here](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).<br> |
| Provide the model to an app such as [Mochi Diffusion](https://github.com/godly-devotion/MochiDiffusion) 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. |
|
|
| # 🧩 Paper Cut model V1 |
| This is the fine-tuned Stable Diffusion model trained on Paper Cut images. |
|
|
| Use **PaperCut** in your prompts. |
|
|
| ### Sample images: |
|  |
|  |
| Based on StableDiffusion 1.5 model |
|
|
| ### 🧨 Diffusers |
|
|
| This model can be used just like any other Stable Diffusion model. For more information, |
| please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion). |
|
|
| You can also export the model to [ONNX](https://huggingface.co/docs/diffusers/optimization/onnx), [MPS](https://huggingface.co/docs/diffusers/optimization/mps) and/or [FLAX/JAX](). |
|
|
| ```python |
| from diffusers import StableDiffusionPipeline |
| import torch |
| |
| model_id = "Fictiverse/Stable_Diffusion_PaperCut_Model" |
| pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
| pipe = pipe.to("cuda") |
| |
| prompt = "PaperCut R2-D2" |
| image = pipe(prompt).images[0] |
| |
| image.save("./R2-D2.png") |
| ``` |
|
|
| ### ✨ Community spotlight : |
| @PiyarSquare : |
| [](https://www.youtube.com/watch?v=wQWHnZlxFj8) |
