How to use from the
Use from the
Diffusers library
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("hgutjh/DeArm")

prompt = "UNICODE\u0000\u0000H\u0000i\u0000g\u0000h\u0000 \u0000r\u0000e\u0000s\u0000 \u0000w\u0000a\u0000i\u0000s\u0000t\u0000 \u0000u\u0000p\u0000 \u0000p\u0000o\u0000r\u0000t\u0000r\u0000a\u0000i\u0000t\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000 \u0000o\u0000f\u0000 \u0000a\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000g\u0000l\u0000i\u0000t\u0000t\u0000e\u0000r\u0000y\u0000 \u0000e\u0000y\u0000e\u0000-\u0000s\u0000h\u0000a\u0000d\u0000o\u0000w\u0000 \u0000a\u0000n\u0000d\u0000 \u0000c\u0000l\u0000e\u0000a\u0000r\u0000 \u0000g\u0000l\u0000o\u0000s\u0000s\u0000y\u0000 \u0000l\u0000i\u0000p\u0000-\u0000g\u0000l\u0000o\u0000s\u0000s\u0000.\u0000 \u0000S\u0000h\u0000e\u0000 \u0000i\u0000s\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000a\u0000t\u0000 \u0000t\u0000h\u0000e\u0000 \u0000v\u0000i\u0000e\u0000w\u0000e\u0000r\u0000 \u0000w\u0000i\u0000t\u0000h\u0000 \u0000h\u0000e\u0000r\u0000 \u0000m\u0000o\u0000u\u0000t\u0000h\u0000 \u0000c\u0000l\u0000o\u0000s\u0000e\u0000d\u0000.\u0000 \u0000S\u0000h\u0000e\u0000 \u0000i\u0000s\u0000 \u0000w\u0000e\u0000a\u0000r\u0000i\u0000n\u0000g\u0000 \u0000a\u0000 \u0000t\u0000h\u0000i\u0000n\u0000 \u0000s\u0000t\u0000r\u0000i\u0000n\u0000g\u0000-\u0000l\u0000i\u0000k\u0000e\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000c\u0000h\u0000o\u0000k\u0000e\u0000r\u0000 \u0000a\u0000n\u0000d\u0000 \u0000h\u0000o\u0000o\u0000p\u0000 \u0000e\u0000a\u0000r\u0000r\u0000i\u0000n\u0000g\u0000s\u0000.\u0000 \u0000I\u0000n\u0000 \u0000t\u0000h\u0000e\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000 \u0000i\u0000s\u0000 \u0000a\u0000 \u0000n\u0000i\u0000g\u0000h\u0000t\u0000c\u0000l\u0000u\u0000b\u0000 \u0000s\u0000c\u0000e\u0000n\u0000e\u0000 \u0000o\u0000u\u0000t\u0000 \u0000o\u0000f\u0000 \u0000f\u0000o\u0000c\u0000u\u0000s\u0000.\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000A\u0000a\u0000_\u0000d\u0000e\u0000_\u0000A\u0000r\u0000m\u0000a\u0000s\u0000_\u0000F\u0000L\u0000U\u0000X\u0000_\u0000v\u00005\u0000-\u0000m\u0000e\u0000r\u0000g\u0000e\u0000r\u0000_\u00003\u00007\u0000_\u00005\u00003\u0000_\u00006\u00005\u0000_\u00000\u00002\u0000_\u00000\u00003\u0000_\u00000\u00005\u0000:\u00001\u0000>\u0000"
image = pipe(prompt).images[0]

DeArm

Prompt
UNICODEHigh res waist up portrait photo of a woman with glittery eye-shadow and clear glossy lip-gloss. She is looking at the viewer with her mouth closed. She is wearing a thin string-like black choker and hoop earrings. In the background is a nightclub scene out of focus., <lora:Aa_de_Armas_FLUX_v5-merger_37_53_65_02_03_05:1>

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

Downloads last month
4
Inference Providers NEW
Examples

Model tree for hgutjh/DeArm

Adapter
(42615)
this model