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--- |
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language: zh |
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license: creativeml-openrail-m |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- multilingual |
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- English(En) |
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- Chinese(Zh) |
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- Spanish(Es) |
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- French(Fr) |
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- Russian(Ru) |
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- Japanese(Ja) |
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- Korean(Ko) |
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- Arabic(Ar) |
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- Italian(It) |
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- diffusers |
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widget: |
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- text: "一张<鸣人>男孩的照片" |
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example_title: 一张<鸣人>男孩的照片 |
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--- |
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# This is a DreamBooth model finetuned from the multilingual text-to-image model AltDiffusion. |
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Dreambooth is one of the method of finetune the pretrained text-to-image model.Given as input just a few images of a subject, it learns to bind a unique identifier with that specific subject. |
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AltDiffusion which is a multilingual text-to-image model.It currently supports 9 languages and will support more in future. |
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We can use the dreambooth to finetune the AltDiffusion,so that we can get a multilingual Dreambooth model which could supports 9 languages. |
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Here we give a example model finetuned use a dozen pictures of Uzumaki Naruto downloaded from web.The example code of inference is shown bellow.You can have a try and maybe train your own dreambooth.Hopes have fun! |
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## Example code of inference |
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``` |
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from diffusers import AltDiffusionPipeline, DPMSolverMultistepScheduler |
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import torch |
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pipe = AltDiffusionPipeline.from_pretrained("BAAI/DreamBooth-AltDiffusion") |
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pipe = pipe.to("cuda") |
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config) |
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prompt = "一张<鸣人>男孩的照片" |
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image = pipe(prompt, num_inference_steps=25).images[0] |
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image.show() |
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``` |
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