import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("mulanai/mulan-lang-adapter", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]MuLan Language Adapter
What is it ?
We present MuLan, a versatile framework to equip any diffusion model with multilingual generation abilities natively by up to 110+ languages around the world. With properly trained text encoder from noisy data, we demonstrate that MuLan could be trained on English only data and support other languages zero-shot. Additionally, we introduce Language Adapter. A language adapter with less than 20M parameters, trained against a frozen denoiser and a text encoder, can be readily combined with any homologous community models/tools, such as LoRA, LCM, ControlNet, and IP-Adapter, without any finetuning.
https://github.com/mulanai/MuLan
Examples:
# pip install mulankit
from diffusers import StableDiffusionPipeline
+ import mulankit
pipe = StableDiffusionPipeline.from_pretrained('Lykon/dreamshaper-8')
+ pipe = mulankit.transform(pipe, 'mulanai/mulan-lang-adapter::sd15_aesthetic.pth')
image = pipe('ไธๅช่่ฒ็๐ถ in the ๋ฐ๋ค').images[0]
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