Instructions to use Trenddwdw/Dua_Lipa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Trenddwdw/Dua_Lipa 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("Trenddwdw/Dua_Lipa") prompt = "UNICODE\u0000\u0000C\u0000a\u0000n\u0000d\u0000i\u0000d\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000o\u0000f\u0000 \u0000a\u0000 \u0000p\u0000i\u0000r\u0000a\u0000t\u0000e\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000l\u0000o\u0000n\u0000g\u0000 \u0000w\u0000a\u0000v\u0000y\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000h\u0000a\u0000i\u0000r\u0000 \u0000i\u0000n\u0000 \u0000t\u0000h\u0000e\u0000 \u0000s\u0000e\u0000e\u0000 \u0000b\u0000r\u0000e\u0000e\u0000z\u0000e\u0000 \u0000s\u0000t\u0000a\u0000n\u0000d\u0000i\u0000n\u0000g\u0000 \u0000o\u0000n\u0000 \u0000t\u0000h\u0000e\u0000 \u0000f\u0000r\u0000o\u0000n\u0000t\u0000 \u0000m\u0000a\u0000s\u0000t\u0000 \u0000o\u0000f\u0000 \u0000a\u0000 \u0000p\u0000i\u0000r\u0000a\u0000t\u0000e\u0000 \u0000s\u0000h\u0000i\u0000p\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000c\u0000o\u0000n\u0000t\u0000e\u0000n\u0000t\u0000l\u0000y\u0000 \u0000i\u0000n\u0000t\u0000o\u0000 \u0000t\u0000h\u0000e\u0000 \u0000d\u0000i\u0000s\u0000t\u0000a\u0000n\u0000c\u0000e\u0000.\u0000 \u0000S\u0000h\u0000e\u0000 \u0000i\u0000s\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000a\u0000 \u0000p\u0000i\u0000r\u0000a\u0000t\u0000e\u0000'\u0000s\u0000 \u0000h\u0000a\u0000t\u0000 \u0000a\u0000n\u0000d\u0000 \u0000h\u0000a\u0000s\u0000 \u0000a\u0000 \u0000r\u0000a\u0000p\u0000i\u0000e\u0000r\u0000 \u0000s\u0000w\u0000o\u0000r\u0000d\u0000 \u0000s\u0000t\u0000r\u0000a\u0000p\u0000p\u0000e\u0000d\u0000 \u0000t\u0000o\u0000 \u0000h\u0000e\u0000r\u0000 \u0000w\u0000a\u0000i\u0000s\u0000t\u0000.\u0000 \u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000D\u0000u\u0000a\u0000_\u0000L\u0000i\u0000p\u0000a\u0000_\u0000n\u0000e\u0000w\u0000_\u0000F\u0000L\u0000U\u0000X\u0000_\u0000v\u00002\u0000-\u00000\u00000\u00000\u00000\u00005\u00005\u0000:\u00001\u0000>\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Dua_Lipa

- Prompt
- UNICODECandid photo of a pirate woman with long wavy black hair in the see breeze standing on the front mast of a pirate ship looking contently into the distance. She is wearing a pirate's hat and has a rapier sword strapped to her waist. , <lora:Dua_Lipa_new_FLUX_v2-000055:1>

- Prompt
- UNICODEHigh quality passport photo of a woman wearing a suit and tie looking directly at the camera with her mouth closed and a neutral expression. She is also wearing a delicate gold chain and some understated diamond earrings. , <lora:Dua_Lipa_new_FLUX_v2-000055:1>
Trigger words
You should use Dua_Lipa to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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