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--- |
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license: creativeml-openrail-m |
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thumbnail: "https://huggingface.co/coreml/coreml-anything-v3-1/resolve/main/example-images/thumbnail.png" |
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language: |
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- en |
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tags: |
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- coreml |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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--- |
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# Core ML Converted Model |
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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> |
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Provide the model to an app such as [Mochi Diffusion](https://github.com/godly-devotion/MochiDiffusion) to generate images.<br> |
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`split_einsum` version is compatible with all compute unit options including Neural Engine.<br> |
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`original` version is only compatible with CPU & GPU option. |
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# 🧩 Paper Cut model V1 |
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This is the fine-tuned Stable Diffusion model trained on Paper Cut images. |
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Use **PaperCut** in your prompts. |
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### Sample images: |
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Based on StableDiffusion 1.5 model |
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### 🧨 Diffusers |
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This model can be used just like any other Stable Diffusion model. For more information, |
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please have a look at the [Stable Diffusion](https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion). |
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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](). |
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```python |
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from diffusers import StableDiffusionPipeline |
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import torch |
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model_id = "Fictiverse/Stable_Diffusion_PaperCut_Model" |
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pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) |
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pipe = pipe.to("cuda") |
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prompt = "PaperCut R2-D2" |
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image = pipe(prompt).images[0] |
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image.save("./R2-D2.png") |
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``` |
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### ✨ Community spotlight : |
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@PiyarSquare : |
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[](https://www.youtube.com/watch?v=wQWHnZlxFj8) |
