import torch
from diffusers import FluxPipeline
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to("npu")
prompt = "A cat holding a sign that says hello world"
image = pipe(
 prompt,
 height=1024,
 width=1024,
 guidance_scale=3.5,
 num_inference_steps=50,
 max_sequence_length=512,
 generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev.png")

import torch
from diffusers import FluxFillPipeline
from diffusers.utils import load_image
image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")
pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("npu")
image = pipe(
 prompt="a white paper cup",
 image=image,
 mask_image=mask,
 height=1632,
 width=1232,
 guidance_scale=30,
 num_inference_steps=50,
 max_sequence_length=512,
 generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save(f"flux-fill-dev.png")