| | --- |
| | 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) |
