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SanaControlNetPipeline with 🧨diffusers1# run `pip install git+https://github.com/huggingface/diffusers` before use Sana in diffusers
2import torch
3from diffusers import SanaControlNetModel, SanaControlNetPipeline
4from diffusers.utils import load_image
5
6pipe = SanaControlNetPipeline.from_pretrained(
7 "ishan24/Sana_600M_1024px_ControlNetPlus_diffusers",
8 variant="fp16",
9 torch_dtype=torch.float16,
10 device_map="balanced"
11)
12
13pipe.vae.to(torch.bfloat16)
14pipe.text_encoder.to(torch.bfloat16)
15
16cond_image = load_image(
17 "https://huggingface.co/ishan24/Sana_600M_1024px_ControlNet_diffusers/resolve/main/hed_example.png"
18)
19prompt='a cat with a neon sign that says "Sana"'
20image = pipe(
21 prompt,
22 control_image=cond_image,
23).images[0]
24image.save("sana.png")