readme: ---
  language: zh
  license: creativeml-openrail-m
  
  tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - multilingual
  - English(En)
  - Chinese(Zh)
  - Spanish(Es)
  - French(Fr)
  - Russian(Ru)
  - Japanese(Ja)
  - Korean(Ko)
  - Arabic(Ar)
  - Italian(It)
  - diffusers
  
  widget:
  - text: "一张<鸣人>男孩的照片"
    example_title: 一张<鸣人>男孩的照片
  ---
  
  # This is a DreamBooth model finetuned from the multilingual text-to-image model AltDiffusion.
  
  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.
  
  AltDiffusion which is a multilingual text-to-image model.It currently supports 9 languages and will support more in future.
  We can use the dreambooth to finetune the AltDiffusion,so that we can get a multilingual Dreambooth model which could supports 9 languages.
  
  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!
  
  ## Example code of inference
  ```
  from diffusers import AltDiffusionPipeline, DPMSolverMultistepScheduler
  import torch
  
  pipe = AltDiffusionPipeline.from_pretrained("BAAI/DreamBooth-AltDiffusion")
  pipe = pipe.to("cuda")
  
  pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
  
  prompt = "一张<鸣人>男孩的照片"
  image = pipe(prompt, num_inference_steps=25).images[0]
  image.show()
  ```
  