Instructions to use kashansean/shanayakapoor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kashansean/shanayakapoor with Diffusers:
pip install -U diffusers transformers accelerate
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("kashansean/shanayakapoor") prompt = "UNICODE\u0000\u0000f\u0000u\u0000l\u0000l\u0000 \u0000b\u0000o\u0000d\u0000y\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000o\u0000f\u0000 \u0000S\u0000h\u0000a\u0000n\u0000a\u0000y\u0000a\u0000 \u0000K\u0000a\u0000p\u0000o\u0000o\u0000r\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000,\u0000h\u0000y\u0000p\u0000e\u0000r\u0000 \u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000 \u0000c\u0000a\u0000n\u0000d\u0000i\u0000d\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000,\u0000 \u0000s\u0000h\u0000o\u0000u\u0000t\u0000i\u0000n\u0000g\u0000,\u0000s\u0000t\u0000u\u0000d\u0000i\u0000o\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000i\u0000n\u0000t\u0000r\u0000i\u0000c\u0000a\u0000t\u0000e\u0000 \u0000c\u0000o\u0000n\u0000s\u0000e\u0000r\u0000v\u0000a\u0000t\u0000i\u0000v\u0000e\u0000 \u0000t\u0000u\u0000r\u0000t\u0000l\u0000e\u0000n\u0000e\u0000c\u0000k\u0000 \u0000L\u0000i\u0000m\u0000e\u0000 \u0000G\u0000r\u0000e\u0000e\u0000n\u0000 \u0000S\u0000h\u0000a\u0000r\u0000a\u0000r\u0000a\u0000 \u0000S\u0000u\u0000i\u0000t\u0000,\u0000 \u0000c\u0000u\u0000r\u0000l\u0000s\u0000,\u0000 \u0000p\u0000a\u0000s\u0000t\u0000e\u0000l\u0000 \u0000s\u0000h\u0000a\u0000d\u0000e\u0000d\u0000 \u0000m\u0000u\u0000l\u0000t\u0000i\u0000c\u0000o\u0000l\u0000o\u0000r\u0000e\u0000d\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000,\u0000 \u0000c\u0000i\u0000n\u0000e\u0000m\u0000a\u0000t\u0000i\u0000c\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000i\u0000n\u0000g\u0000 \u0000 \u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000S\u0000h\u0000a\u0000n\u0000a\u0000y\u0000a\u0000_\u0000K\u0000a\u0000p\u0000o\u0000o\u0000r\u0000_\u0000F\u0000l\u0000u\u0000x\u0000_\u0000K\u0000o\u0000h\u0000y\u0000a\u0000_\u0000L\u0000o\u0000R\u0000A\u0000_\u0000v\u00001\u0000-\u00000\u00000\u00000\u00000\u00000\u00003\u0000:\u00001\u0000> \u000b \u000b \u000b\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Shanaya

- Prompt
- UNICODEfull body photo of Shanaya Kapoor woman,hyper realistic candid photo, shouting,studio quality, wearing intricate conservative turtleneck Lime Green Sharara Suit, curls, pastel shaded multicolored background, cinematic lighting <lora:Shanaya_Kapoor_Flux_Kohya_LoRA_v1-000003:1>
Trigger words
You should use shanaya kapoor 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
- 17