import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("diffusers/controlnet-canny-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("WebCrep/WC")
prompt = "UNICODE\u0000\u0000g\u0000e\u0000i\u0000s\u0000h\u0000a\u0000,\u0000 \u0000s\u0000o\u0000f\u0000t\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000,\u0000 \u0000g\u0000o\u0000r\u0000g\u0000e\u0000o\u0000u\u0000s\u0000,\u0000 \u0000m\u0000y\u0000s\u0000t\u0000i\u0000c\u0000a\u0000l\u0000,\u0000 \u0000r\u0000e\u0000d\u0000 \u0000l\u0000i\u0000p\u0000s\u0000 \u0000a\u0000n\u0000d\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000a\u0000 \u0000t\u0000r\u0000a\u0000d\u0000i\u0000t\u0000i\u0000o\u0000n\u0000a\u0000l\u0000 \u0000j\u0000a\u0000p\u0000a\u0000n\u0000e\u0000s\u0000e\u0000 \u0000k\u0000i\u0000m\u0000o\u0000n\u0000o\u0000,\u0000 \u0000i\u0000n\u0000 \u0000g\u0000l\u0000a\u0000s\u0000s\u0000e\u0000s\u0000,\u0000 \u0000b\u0000y\u0000 \u0000 \u0000a\u0000l\u0000b\u0000e\u0000r\u0000t\u0000o\u0000m\u0000i\u0000e\u0000l\u0000g\u0000o\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000A\u0000l\u0000b\u0000e\u0000r\u0000t\u0000o\u0000M\u0000i\u0000e\u0000l\u0000g\u0000o\u0000_\u0000s\u0000t\u0000y\u0000l\u0000e\u0000_\u0000S\u0000D\u0000X\u0000L\u0000:\u00000\u0000.\u00009\u0000>\u0000"
image = pipe(prompt).images[0]similar to A. Mielgo Style SDXL
- Prompt
- UNICODEgeisha, soft background, gorgeous, mystical, red lips and black hair, wearing a traditional japanese kimono, in glasses, by albertomielgo <lora:AlbertoMielgo_style_SDXL:0.9>
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for WebCrep/WC
Base model
runwayml/stable-diffusion-v1-5 Finetuned
diffusers/controlnet-canny-sdxl-1.0