Instructions to use davkap92/flux.david with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use davkap92/flux.david 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("davkap92/flux.david") prompt = "UNICODE\u0000\u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000d\u0000k\u0000-\u0000p\u0000e\u0000r\u0000s\u0000o\u0000n\u0000-\u00002\u00002\u0000:\u00001\u0000>\u0000 \u0000A\u0000 \u0000p\u0000r\u0000o\u0000f\u0000e\u0000s\u0000s\u0000i\u0000o\u0000n\u0000a\u0000l\u0000 \u0000h\u0000e\u0000a\u0000d\u0000s\u0000h\u0000o\u0000t\u0000 \u0000o\u0000f\u0000 \u0000p\u00003\u0000r\u0000s\u00000\u0000n\u0000,\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000a\u0000 \u0000s\u0000m\u0000a\u0000r\u0000t\u0000-\u0000c\u0000a\u0000s\u0000u\u0000a\u0000l\u0000 \u0000o\u0000u\u0000t\u0000f\u0000i\u0000t\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000a\u0000 \u0000n\u0000e\u0000u\u0000t\u0000r\u0000a\u0000l\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000.\u0000 \u0000T\u0000h\u0000e\u0000 \u0000m\u0000a\u0000n\u0000 \u0000i\u0000s\u0000 \u0000s\u0000m\u0000i\u0000l\u0000i\u0000n\u0000g\u0000 \u0000c\u0000o\u0000n\u0000f\u0000i\u0000d\u0000e\u0000n\u0000t\u0000l\u0000y\u0000,\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000d\u0000i\u0000r\u0000e\u0000c\u0000t\u0000l\u0000y\u0000 \u0000a\u0000t\u0000 \u0000t\u0000h\u0000e\u0000 \u0000c\u0000a\u0000m\u0000e\u0000r\u0000a\u0000.\u0000 \u0000N\u0000a\u0000t\u0000u\u0000r\u0000a\u0000l\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000i\u0000n\u0000g\u0000 \u0000e\u0000m\u0000p\u0000h\u0000a\u0000s\u0000i\u0000z\u0000e\u0000s\u0000 \u0000h\u0000i\u0000s\u0000 \u0000f\u0000a\u0000c\u0000i\u0000a\u0000l\u0000 \u0000f\u0000e\u0000a\u0000t\u0000u\u0000r\u0000e\u0000s\u0000.\u0000 \u0000T\u0000h\u0000e\u0000 \u0000i\u0000m\u0000a\u0000g\u0000e\u0000 \u0000h\u0000a\u0000s\u0000 \u0000a\u0000 \u0000m\u0000o\u0000d\u0000e\u0000r\u0000n\u0000,\u0000 \u0000p\u0000o\u0000l\u0000i\u0000s\u0000h\u0000e\u0000d\u0000 \u0000l\u0000o\u0000o\u0000k\u0000,\u0000 \u0000s\u0000u\u0000i\u0000t\u0000a\u0000b\u0000l\u0000e\u0000 \u0000f\u0000o\u0000r\u0000 \u0000a\u0000 \u0000L\u0000i\u0000n\u0000k\u0000e\u0000d\u0000I\u0000n\u0000 \u0000p\u0000r\u0000o\u0000f\u0000i\u0000l\u0000e\u0000.\u0000 \u0000T\u0000h\u0000e\u0000 \u0000c\u0000o\u0000m\u0000p\u0000o\u0000s\u0000i\u0000t\u0000i\u0000o\u0000n\u0000 \u0000i\u0000s\u0000 \u0000c\u0000e\u0000n\u0000t\u0000e\u0000r\u0000e\u0000d\u0000,\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000a\u0000 \u0000s\u0000u\u0000b\u0000t\u0000l\u0000e\u0000 \u0000d\u0000e\u0000p\u0000t\u0000h\u0000 \u0000o\u0000f\u0000 \u0000f\u0000i\u0000e\u0000l\u0000d\u0000 \u0000t\u0000o\u0000 \u0000b\u0000l\u0000u\u0000r\u0000 \u0000t\u0000h\u0000e\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000 \u0000w\u0000h\u0000i\u0000l\u0000e\u0000 \u0000k\u0000e\u0000e\u0000p\u0000i\u0000n\u0000g\u0000 \u0000t\u0000h\u0000e\u0000 \u0000s\u0000u\u0000b\u0000j\u0000e\u0000c\u0000t\u0000 \u0000i\u0000n\u0000 \u0000s\u0000h\u0000a\u0000r\u0000p\u0000 \u0000f\u0000o\u0000c\u0000u\u0000s\u0000.\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
dsk
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- Prompt
- UNICODE<lora:dk-person-22:1> A professional headshot of p3rs0n, wearing a smart-casual outfit with a neutral background. The man is smiling confidently, looking directly at the camera. Natural lighting emphasizes his facial features. The image has a modern, polished look, suitable for a LinkedIn profile. The composition is centered, with a subtle depth of field to blur the background while keeping the subject in sharp focus.
Model description
Model of p3rs0n - david
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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