import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-XL-v9", torch_dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("sohancec/Desi-Lora")
prompt = "UNICODE\u0000\u0000U\u0000l\u0000t\u0000r\u0000a\u0000 \u0000h\u0000i\u0000g\u0000h\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000 \u0000u\u0000l\u0000t\u0000r\u0000a\u0000 \u0000h\u0000i\u0000g\u0000h\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000M\u0000a\u0000s\u0000t\u0000e\u0000r\u0000p\u0000i\u0000e\u0000c\u0000e\u0000,\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000,\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000b\u0000e\u0000s\u0000t\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000C\u0000o\u0000l\u0000l\u0000a\u0000p\u0000s\u0000e\u0000d\u0000 \u0000s\u0000k\u0000y\u0000s\u0000c\u0000r\u0000a\u0000p\u0000e\u0000r\u0000 \u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000b\u0000u\u0000r\u0000n\u0000i\u0000n\u0000g\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000m\u0000a\u0000s\u0000s\u0000i\u0000v\u0000e\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000S\u0000c\u0000i\u0000f\u0000i\u0000 \u0000c\u0000i\u0000t\u0000y\u0000r\u0000u\u0000i\u0000n\u0000s\u0000,\u0000 \u0000"
image = pipe(prompt).images[0]Indian-Lora
- Prompt
- UNICODEUltra high detail, ultra high quality, Masterpiece, photorealistic, quality, best detail, Collapsed skyscraper ruins, burning cityruins, massive cityruins, Scifi cityruins,
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Model tree for sohancec/Desi-Lora
Base model
stabilityai/stable-diffusion-xl-base-1.0 Finetuned
RunDiffusion/Juggernaut-XL-v9