Text-to-Image
Diffusers
TensorBoard
Chinese
AltDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
multilingual
English(En)
Chinese(Zh)
Spanish(Es)
French(Fr)
Russian(Ru)
Japanese(Ja)
Korean(Ko)
Arabic(Ar)
Italian(It)
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("BAAI/DreamBooth-AltDiffusion", dtype=torch.bfloat16, device_map="cuda")
prompt = "一张<鸣人>男孩的照片"
image = pipe(prompt).images[0]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()
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