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--- |
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language: |
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- en |
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license: creativeml-openrail-m |
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thumbnail: "https://huggingface.co/Guizmus/Tardisfusion/resolve/main/showcase.jpg" |
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tags: |
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- stable-diffusion |
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- text-to-image |
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- image-to-image |
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- DrWho |
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library_name: "https://github.com/ShivamShrirao/diffusers" |
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inference: false |
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--- |
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# TARDISfusion |
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<p> |
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<img src="https://huggingface.co/Guizmus/Tardisfusion/raw/main/showcase.jpg"/><br/> |
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This is a Dreamboothed Stable Diffusion model trained on 3 Style concepts.<br/> |
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The total dataset is made of 209 pictures, and the training has been done on runawayml 1.5 with 2500 steps and the new VAE. |
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The following tokens will add their corresponding concept :<br/> |
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<ul> |
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<li><b>Classic Tardis style</b> : Architectural and furniture style seen inside the TARDIS in the series before the reboot.</li> |
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<li><b>Modern Tardis style</b>: Architectural and furniture style seen inside the TARDIS in the series after the reboot</li> |
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<li><b>Tardis Box style</b>: A style made from the TARDIS seen from the outside. Summons a TARDIS anywhere.</li> |
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</ul> |
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</p> |
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[CKPT download link](https://huggingface.co/Guizmus/Tardisfusion/resolve/main/Tardisfusion-v2.ckpt) |
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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 = "Guizmus/Tardisfusion" |
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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 = "a bedroom, Classic Tardis style" |
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image = pipe(prompt).images[0] |
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image.save("./TARDIS Style.png") |
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``` |
