import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("sridevshenoy/seetha")
prompt = "UNICODE\u0000\u0000l\u0000o\u0000n\u0000g\u0000 \u0000s\u0000h\u0000o\u0000t\u0000 \u0000s\u0000c\u0000e\u0000n\u0000i\u0000c\u0000 \u0000p\u0000r\u0000o\u0000f\u0000e\u0000s\u0000s\u0000i\u0000o\u0000n\u0000a\u0000l\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000g\u0000r\u0000a\u0000p\u0000h\u0000 \u0000o\u0000f\u0000 \u0000b\u0000o\u0000r\u0000s\u0000e\u0000 \u0000s\u0000i\u0000t\u0000t\u0000i\u0000n\u0000g\u0000 \u0000o\u0000n\u0000 \u0000b\u0000e\u0000d\u0000 \u0000,\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000r\u0000e\u0000d\u0000 \u0000s\u0000a\u0000r\u0000e\u0000e\u0000 \u0000l\u0000a\u0000u\u0000g\u0000h\u0000i\u0000n\u0000g\u0000,\u0000 \u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000b\u0000h\u0000a\u0000g\u0000y\u0000a\u0000s\u0000h\u0000r\u0000i\u0000-\u0000b\u0000o\u0000r\u0000s\u0000e\u0000-\u00000\u00000\u00000\u00000\u00000\u00008\u0000:\u00001\u0000>\u0000 \u0000,\u0000 \u0000p\u0000e\u0000r\u0000f\u0000e\u0000c\u0000t\u0000 \u0000v\u0000i\u0000e\u0000w\u0000p\u0000o\u0000i\u0000n\u0000t\u0000,\u0000 \u0000h\u0000i\u0000g\u0000h\u0000l\u0000y\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000e\u0000d\u0000,\u0000 \u0000w\u0000i\u0000d\u0000e\u0000-\u0000a\u0000n\u0000g\u0000l\u0000e\u0000 \u0000l\u0000e\u0000n\u0000s\u0000,\u0000 \u0000h\u0000y\u0000p\u0000e\u0000r\u0000 \u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000,\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000d\u0000r\u0000a\u0000m\u0000a\u0000t\u0000i\u0000c\u0000 \u0000s\u0000k\u0000y\u0000,\u0000 \u0000p\u0000o\u0000l\u0000a\u0000r\u0000i\u0000z\u0000i\u0000n\u0000g\u0000 \u0000f\u0000i\u0000l\u0000t\u0000e\u0000r\u0000,\u0000 \u0000n\u0000a\u0000t\u0000u\u0000r\u0000a\u0000l\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000i\u0000n\u0000g\u0000,\u0000 \u0000v\u0000i\u0000v\u0000i\u0000d\u0000 \u0000c\u0000o\u0000l\u0000o\u0000r\u0000s\u0000,\u0000 \u0000e\u0000v\u0000e\u0000r\u0000y\u0000t\u0000h\u0000i\u0000n\u0000g\u0000 \u0000i\u0000n\u0000 \u0000s\u0000h\u0000a\u0000r\u0000p\u0000 \u0000f\u0000o\u0000c\u0000u\u0000s\u0000,\u0000 \u0000H\u0000D\u0000R\u0000,\u0000 \u0000U\u0000H\u0000D\u0000,\u0000 \u00006\u00004\u0000K\u0000"
image = pipe(prompt).images[0]seetha
- Prompt
- UNICODElong shot scenic professional photograph of borse sitting on bed , wearing red saree laughing, <lora:bhagyashri-borse-000008:1> , perfect viewpoint, highly detailed, wide-angle lens, hyper realistic, with dramatic sky, polarizing filter, natural lighting, vivid colors, everything in sharp focus, HDR, UHD, 64K
Trigger words
You should use Indian beauty to trigger the image generation.
You should use most beautiful and attractive to trigger the image generation.
You should use sexy body to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
- Downloads last month
- 1
Model tree for sridevshenoy/seetha
Base model
black-forest-labs/FLUX.1-dev