Instructions to use Shero448/erza with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shero448/erza with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("John6666/prefect-pony-xl-v2-cleaned-style-sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Shero448/erza") prompt = "UNICODE\u0000\u0000 \u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00009\u0000,\u0000 \u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00008\u0000_\u0000u\u0000p\u0000,\u0000 \u0000s\u0000c\u0000o\u0000r\u0000e\u0000_\u00007\u0000_\u0000u\u0000p\u0000,\u0000 \u0000s\u0000o\u0000u\u0000r\u0000c\u0000e\u0000_\u0000a\u0000n\u0000i\u0000m\u0000e\u0000,\u0000 \u0000e\u0000r\u0000z\u0000a\u0000s\u0000c\u0000a\u0000r\u0000l\u0000e\u0000t\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000e\u0000r\u0000z\u0000a\u0000-\u0000s\u0000c\u0000a\u0000r\u0000l\u0000e\u0000t\u0000-\u0000p\u0000o\u0000n\u0000y\u0000x\u0000l\u0000-\u0000l\u0000o\u0000r\u0000a\u0000-\u0000n\u0000o\u0000c\u0000h\u0000e\u0000k\u0000a\u0000i\u0000s\u0000e\u0000r\u0000:\u00001\u0000>\u0000 \u0000e\u0000r\u0000z\u0000a\u0000 \u0000s\u0000c\u0000a\u0000r\u0000l\u0000e\u0000t\u0000,\u0000 \u0000l\u0000o\u0000n\u0000g\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000r\u0000e\u0000d\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000h\u0000a\u0000i\u0000r\u0000 \u0000b\u0000e\u0000t\u0000w\u0000e\u0000e\u0000n\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000b\u0000r\u0000o\u0000w\u0000n\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u00001\u0000g\u0000i\u0000r\u0000l\u0000,\u0000 \u0000b\u0000i\u0000g\u0000_\u0000b\u0000r\u0000e\u0000a\u0000s\u0000t\u0000s\u0000,\u0000 \u0000t\u0000i\u0000t\u0000s\u0000 \u0000c\u0000o\u0000m\u0000e\u0000 \u0000o\u0000u\u0000t\u0000 \u0000o\u0000f\u0000 \u0000t\u0000h\u0000e\u0000 \u0000d\u0000r\u0000e\u0000s\u0000s\u0000,\u0000 \u0000b\u0000r\u0000o\u0000w\u0000n\u0000_\u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000r\u0000e\u0000d\u0000_\u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000s\u0000e\u0000x\u0000y\u0000 \u0000b\u0000l\u0000u\u0000e\u0000 \u0000l\u0000a\u0000t\u0000e\u0000x\u0000 \u0000b\u0000i\u0000k\u0000i\u0000n\u0000i\u0000,\u0000 \u0000j\u0000e\u0000w\u0000e\u0000l\u0000r\u0000y\u0000 \u0000(\u0000r\u0000i\u0000n\u0000g\u0000s\u0000 \u0000a\u0000n\u0000d\u0000 \u0000e\u0000a\u0000r\u0000r\u0000i\u0000n\u0000g\u0000s\u0000)\u0000 \u0000l\u0000o\u0000o\u0000k\u0000i\u0000n\u0000g\u0000 \u0000a\u0000t\u0000 \u0000v\u0000i\u0000e\u0000w\u0000e\u0000r\u0000,\u0000 \u0000s\u0000m\u0000i\u0000r\u0000k\u0000,\u0000 \u0000d\u0000y\u0000n\u0000a\u0000m\u0000i\u0000c\u0000 \u0000a\u0000n\u0000g\u0000l\u0000e\u0000,\u0000 \u0000d\u0000r\u0000a\u0000m\u0000a\u0000t\u0000i\u0000c\u0000 \u0000l\u0000i\u0000g\u0000h\u0000t\u0000s\u0000,\u0000 \u0000p\u0000o\u0000r\u0000n\u0000,\u0000 \u0000h\u0000a\u0000l\u0000f\u0000 \u0000n\u0000a\u0000k\u0000e\u0000d\u0000,\u0000 \u0000s\u0000a\u0000u\u0000n\u0000a\u0000,\u0000 \u0000w\u0000e\u0000t\u0000,\u0000 \u0000b\u0000o\u0000o\u0000b\u0000s\u0000 \u0000a\u0000g\u0000a\u0000i\u0000n\u0000s\u0000t\u0000 \u0000g\u0000l\u0000a\u0000s\u0000s\u0000,\u0000 \u0000h\u0000a\u0000i\u0000r\u0000 \u0000t\u0000i\u0000e\u0000d\u0000 \u0000b\u0000a\u0000c\u0000k\u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
erza

- Prompt
- UNICODE score_9, score_8_up, score_7_up, source_anime, erzascarlet, <lora:erza-scarlet-ponyxl-lora-nochekaiser:1> erza scarlet, long hair, red hair, hair between eyes, brown eyes, 1girl, big_breasts, tits come out of the dress, brown_eyes, red_hair, sexy blue latex bikini, jewelry (rings and earrings) looking at viewer, smirk, dynamic angle, dramatic lights, porn, half naked, sauna, wet, boobs against glass, hair tied back
Trigger words
You should use erza 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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