import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("CiroN2022/cyber-tech")
prompt = "product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity"
image = pipe(prompt).images[0]Cyber Tech
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
None
Image examples for the model:
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( cyber_tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
product photo, ( retro cyber tech ) , reflective , Ella Guru, f 8 aperture, a 3D render, new objectivity
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stabilityai/stable-diffusion-xl-base-1.0