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--- |
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license: openrail |
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tags: |
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- text-to-image |
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--- |
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# Microscopic model V1 |
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This is the fine-tuned Stable Diffusion model trained on microscopic images. |
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Use **Microscopic** in your prompts. |
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### Sample images: |
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 |
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 |
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Image enhancing : Before/After |
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 |
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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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``` |