Instructions to use B0rghese/Rixie_Quickfang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B0rghese/Rixie_Quickfang with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B0rghese/Rixie_Quickfang") prompt = "\u0000\u0000Q\u0000u\u0000i\u0000c\u0000k\u0000f\u0000a\u0000n\u0000g\u0000,\u0000,\u0000 \u0000q\u0000u\u0000i\u0000c\u0000k\u0000f\u0000a\u0000n\u0000g\u0000,\u0000 \u00001\u0000g\u0000i\u0000r\u0000l\u0000,\u0000 \u0000m\u0000o\u0000u\u0000s\u0000e\u0000 \u0000p\u0000e\u0000r\u0000s\u0000o\u0000n\u0000,\u0000 \u0000m\u0000o\u0000u\u0000s\u0000e\u0000 \u0000e\u0000a\u0000r\u0000s\u0000,\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000f\u0000u\u0000r\u0000,\u0000 \u0000p\u0000e\u0000t\u0000i\u0000t\u0000e\u0000 \u0000g\u0000i\u0000r\u0000l\u0000,\u0000 \u0000m\u0000e\u0000d\u0000i\u0000u\u0000m\u0000 \u0000b\u0000r\u0000e\u0000a\u0000s\u0000t\u0000s\u0000,\u0000 \u0000f\u0000u\u0000r\u0000r\u0000y\u0000 \u0000f\u0000e\u0000m\u0000a\u0000l\u0000e\u0000,\u0000 \u0000s\u0000o\u0000l\u0000o\u0000,\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000a\u0000t\u0000 \u0000v\u0000i\u0000e\u0000w\u0000e\u0000r\u0000,\u0000 \u0000r\u0000e\u0000d\u0000 \u0000e\u0000y\u0000e\u0000,\u0000 \u0000g\u0000r\u0000e\u0000e\u0000n\u0000 \u0000e\u0000y\u0000e\u0000,\u0000 \u0000h\u0000e\u0000t\u0000e\u0000r\u0000o\u0000c\u0000h\u0000r\u0000o\u0000m\u0000i\u0000a\u0000,\u0000 \u0000p\u0000e\u0000r\u0000f\u0000e\u0000c\u0000t\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000f\u0000a\u0000n\u0000g\u0000,\u0000 \u0000s\u0000h\u0000a\u0000r\u0000p\u0000 \u0000t\u0000e\u0000e\u0000t\u0000h\u0000,\u0000 \u0000p\u0000l\u0000a\u0000i\u0000t\u0000e\u0000d\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000d\u0000r\u0000i\u0000l\u0000l\u0000 \u0000t\u0000a\u0000i\u0000l\u0000s\u0000,\u0000 \u0000b\u0000r\u0000a\u0000i\u0000d\u0000s\u0000,\u0000 \u0000m\u0000u\u0000l\u0000t\u0000i\u0000c\u0000o\u0000l\u0000o\u0000r\u0000e\u0000d\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000d\u0000a\u0000r\u0000k\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000g\u0000r\u0000e\u0000e\u0000n\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000p\u0000u\u0000r\u0000p\u0000l\u0000e\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000r\u0000e\u0000d\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000v\u0000e\u0000r\u0000y\u0000 \u0000l\u0000o\u0000n\u0000g\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000s\u0000i\u0000d\u0000e\u0000 \u0000p\u0000a\u0000r\u0000t\u0000 \u0000h\u0000a\u0000i\u0000r\u0000s\u0000t\u0000y\u0000l\u0000e\u0000,\u0000 \u0000m\u0000o\u0000u\u0000s\u0000e\u0000 \u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000l\u0000a\u0000r\u0000g\u0000e\u0000 \u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000m\u0000o\u0000d\u0000e\u0000r\u0000n\u0000 \u0000f\u0000a\u0000n\u0000t\u0000a\u0000s\u0000y\u0000,\u0000 \u0000g\u0000r\u0000i\u0000t\u0000t\u0000y\u0000 \u0000u\u0000n\u0000d\u0000e\u0000r\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000 \u0000s\u0000u\u0000r\u0000v\u0000i\u0000v\u0000a\u0000l\u0000 \u0000c\u0000l\u0000o\u0000t\u0000h\u0000i\u0000n\u0000g\u0000,\u0000 \u0000l\u0000a\u0000y\u0000e\u0000r\u0000e\u0000d\u0000 \u0000s\u0000c\u0000r\u0000a\u0000p\u0000 \u0000w\u0000r\u0000a\u0000p\u0000s\u0000,\u0000 \u0000l\u0000e\u0000a\u0000t\u0000h\u0000e\u0000r\u0000-\u0000s\u0000t\u0000r\u0000a\u0000p\u0000p\u0000e\u0000d\u0000 \u0000c\u0000l\u0000o\u0000t\u0000h\u0000i\u0000n\u0000g\u0000,\u0000 \u0000p\u0000a\u0000t\u0000c\u0000h\u0000w\u0000o\u0000r\u0000k\u0000 \u0000f\u0000a\u0000b\u0000r\u0000i\u0000c\u0000s\u0000,\u0000 \u0000u\u0000t\u0000i\u0000l\u0000i\u0000t\u0000y\u0000 \u0000h\u0000a\u0000r\u0000n\u0000e\u0000s\u0000s\u0000e\u0000s\u0000,\u0000 \u0000t\u0000a\u0000i\u0000l\u0000 \u0000w\u0000r\u0000a\u0000p\u0000s\u0000,\u0000 \u0000a\u0000s\u0000y\u0000m\u0000m\u0000e\u0000t\u0000r\u0000i\u0000c\u0000a\u0000l\u0000 \u0000s\u0000c\u0000a\u0000v\u0000e\u0000n\u0000g\u0000e\u0000d\u0000 \u0000a\u0000r\u0000m\u0000o\u0000r\u0000,\u0000 \u0000h\u0000a\u0000l\u0000f\u0000-\u0000c\u0000l\u0000o\u0000s\u0000e\u0000d\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000b\u0000l\u0000u\u0000s\u0000h\u0000i\u0000n\u0000g\u0000,\u0000 \u0000h\u0000e\u0000a\u0000d\u0000 \u0000t\u0000i\u0000l\u0000t\u0000,\u0000 \u0000e\u0000x\u0000p\u0000r\u0000e\u0000s\u0000s\u0000i\u0000v\u0000e\u0000 \u0000f\u0000a\u0000c\u0000e\u0000,\u0000 \u0000s\u0000m\u0000i\u0000l\u0000e\u0000s\u0000,\u0000 \u0000h\u0000a\u0000p\u0000p\u0000y\u0000,\u0000 \u0000j\u0000o\u0000y\u0000f\u0000u\u0000l\u0000,\u0000 \u0000f\u0000r\u0000i\u0000s\u0000k\u0000y\u0000,\u0000 \u0000c\u0000h\u0000e\u0000e\u0000k\u0000y\u0000,\u0000 \u0000s\u0000a\u0000s\u0000s\u0000y\u0000,\u0000 \u0000s\u0000e\u0000x\u0000y\u0000 \u0000p\u0000o\u0000s\u0000e\u0000,\u0000 \u0000d\u0000y\u0000n\u0000a\u0000m\u0000i\u0000c\u0000 \u0000a\u0000n\u0000g\u0000l\u0000e\u0000,\u0000 \u0000s\u0000i\u0000m\u0000p\u0000l\u0000e\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000,\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000b\u0000a\u0000c\u0000k\u0000g\u0000r\u0000o\u0000u\u0000n\u0000d\u0000,\u0000 \u0000o\u0000p\u0000e\u0000n\u0000 \u0000m\u0000o\u0000u\u0000t\u0000h\u0000,\u0000 \u0000f\u0000r\u0000o\u0000m\u0000 \u0000a\u0000b\u0000o\u0000v\u0000e\u0000,\u0000 \u0000b\u0000o\u0000o\u0000t\u0000s\u0000" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/3H83D6ZEZCX9F1GHS9ZEX3M5S0.jpeg
text: "\0\0Q\0u\0i\0c\0k\0f\0a\0n\0g\0,\0,\0 \0q\0u\0i\0c\0k\0f\0a\0n\0g\0,\0 \01\0g\0i\0r\0l\0,\0 \0m\0o\0u\0s\0e\0 \0p\0e\0r\0s\0o\0n\0,\0 \0m\0o\0u\0s\0e\0 \0e\0a\0r\0s\0,\0 \0w\0h\0i\0t\0e\0 \0f\0u\0r\0,\0 \0p\0e\0t\0i\0t\0e\0 \0g\0i\0r\0l\0,\0 \0m\0e\0d\0i\0u\0m\0 \0b\0r\0e\0a\0s\0t\0s\0,\0 \0f\0u\0r\0r\0y\0 \0f\0e\0m\0a\0l\0e\0,\0 \0s\0o\0l\0o\0,\0 \0l\0o\0o\0k\0i\0n\0g\0 \0a\0t\0 \0v\0i\0e\0w\0e\0r\0,\0 \0r\0e\0d\0 \0e\0y\0e\0,\0 \0g\0r\0e\0e\0n\0 \0e\0y\0e\0,\0 \0h\0e\0t\0e\0r\0o\0c\0h\0r\0o\0m\0i\0a\0,\0 \0p\0e\0r\0f\0e\0c\0t\0 \0e\0y\0e\0s\0,\0 \0f\0a\0n\0g\0,\0 \0s\0h\0a\0r\0p\0 \0t\0e\0e\0t\0h\0,\0 \0p\0l\0a\0i\0t\0e\0d\0 \0h\0a\0i\0r\0,\0 \0d\0r\0i\0l\0l\0 \0t\0a\0i\0l\0s\0,\0 \0b\0r\0a\0i\0d\0s\0,\0 \0m\0u\0l\0t\0i\0c\0o\0l\0o\0r\0e\0d\0 \0h\0a\0i\0r\0,\0 \0d\0a\0r\0k\0 \0h\0a\0i\0r\0,\0 \0g\0r\0e\0e\0n\0 \0h\0a\0i\0r\0,\0 \0p\0u\0r\0p\0l\0e\0 \0h\0a\0i\0r\0,\0 \0r\0e\0d\0 \0h\0a\0i\0r\0,\0 \0w\0h\0i\0t\0e\0 \0h\0a\0i\0r\0,\0 \0v\0e\0r\0y\0 \0l\0o\0n\0g\0 \0h\0a\0i\0r\0,\0 \0s\0i\0d\0e\0 \0p\0a\0r\0t\0 \0h\0a\0i\0r\0s\0t\0y\0l\0e\0,\0 \0m\0o\0u\0s\0e\0 \0t\0a\0i\0l\0,\0 \0l\0a\0r\0g\0e\0 \0t\0a\0i\0l\0,\0 \0m\0o\0d\0e\0r\0n\0 \0f\0a\0n\0t\0a\0s\0y\0,\0 \0g\0r\0i\0t\0t\0y\0 \0u\0n\0d\0e\0r\0g\0r\0o\0u\0n\0d\0 \0s\0u\0r\0v\0i\0v\0a\0l\0 \0c\0l\0o\0t\0h\0i\0n\0g\0,\0 \0l\0a\0y\0e\0r\0e\0d\0 \0s\0c\0r\0a\0p\0 \0w\0r\0a\0p\0s\0,\0 \0l\0e\0a\0t\0h\0e\0r\0-\0s\0t\0r\0a\0p\0p\0e\0d\0 \0c\0l\0o\0t\0h\0i\0n\0g\0,\0 \0p\0a\0t\0c\0h\0w\0o\0r\0k\0 \0f\0a\0b\0r\0i\0c\0s\0,\0 \0u\0t\0i\0l\0i\0t\0y\0 \0h\0a\0r\0n\0e\0s\0s\0e\0s\0,\0 \0t\0a\0i\0l\0 \0w\0r\0a\0p\0s\0,\0 \0a\0s\0y\0m\0m\0e\0t\0r\0i\0c\0a\0l\0 \0s\0c\0a\0v\0e\0n\0g\0e\0d\0 \0a\0r\0m\0o\0r\0,\0 \0h\0a\0l\0f\0-\0c\0l\0o\0s\0e\0d\0 \0e\0y\0e\0s\0,\0 \0b\0l\0u\0s\0h\0i\0n\0g\0,\0 \0h\0e\0a\0d\0 \0t\0i\0l\0t\0,\0 \0e\0x\0p\0r\0e\0s\0s\0i\0v\0e\0 \0f\0a\0c\0e\0,\0 \0s\0m\0i\0l\0e\0s\0,\0 \0h\0a\0p\0p\0y\0,\0 \0j\0o\0y\0f\0u\0l\0,\0 \0f\0r\0i\0s\0k\0y\0,\0 \0c\0h\0e\0e\0k\0y\0,\0 \0s\0a\0s\0s\0y\0,\0 \0s\0e\0x\0y\0 \0p\0o\0s\0e\0,\0 \0d\0y\0n\0a\0m\0i\0c\0 \0a\0n\0g\0l\0e\0,\0 \0s\0i\0m\0p\0l\0e\0 \0b\0a\0c\0k\0g\0r\0o\0u\0n\0d\0,\0 \0w\0h\0i\0t\0e\0 \0b\0a\0c\0k\0g\0r\0o\0u\0n\0d\0,\0 \0o\0p\0e\0n\0 \0m\0o\0u\0t\0h\0,\0 \0f\0r\0o\0m\0 \0a\0b\0o\0v\0e\0,\0 \0b\0o\0o\0t\0s\0"
base_model: krea/Krea-2-Turbo
instance_prompt: quickfang
Rixie Quickfang - Mousegirl Militant [OC]

- Prompt
- Quickfang,, quickfang, 1girl, mouse person, mouse ears, white fur, petite girl, medium breasts, furry female, solo, looking at viewer, red eye, green eye, heterochromia, perfect eyes, fang, sharp teeth, plaited hair, drill tails, braids, multicolored hair, dark hair, green hair, purple hair, red hair, white hair, very long hair, side part hairstyle, mouse tail, large tail, modern fantasy, gritty underground survival clothing, layered scrap wraps, leather-strapped clothing, patchwork fabrics, utility harnesses, tail wraps, asymmetrical scavenged armor, half-closed eyes, blushing, head tilt, expressive face, smiles, happy, joyful, frisky, cheeky, sassy, sexy pose, dynamic angle, simple background, white background, open mouth, from above, boots
Trigger words
You should use quickfang to trigger the image generation.
Download model
Download them in the Files & versions tab.