Instructions to use Arczisan/meimei with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Arczisan/meimei with Diffusers:

pip install -U diffusers transformers accelerate

import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("Arczisan/meimei")

prompt = "UNICODE\u0000\u0000p\u0000h\u0000o\u0000t\u0000o\u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000,\u0000 \u0000(\u00004\u0000k\u0000)\u0000,\u0000 \u0000d\u0000e\u0000p\u0000t\u0000h\u0000 \u0000o\u0000f\u0000 \u0000f\u0000i\u0000e\u0000l\u0000d\u0000,\u0000 \u0000(\u0000M\u0000a\u0000s\u0000t\u0000e\u0000r\u0000p\u0000i\u0000e\u0000c\u0000e\u0000)\u0000,\u0000 \u0000(\u0000r\u0000e\u0000a\u0000l\u0000i\u0000s\u0000t\u0000i\u0000c\u0000 \u0000s\u0000k\u0000i\u0000n\u0000 \u0000t\u0000e\u0000x\u0000t\u0000u\u0000r\u0000e\u0000)\u0000,\u0000 \u0000e\u0000x\u0000t\u0000r\u0000e\u0000m\u0000e\u0000l\u0000y\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000e\u0000d\u0000,\u0000 \u0000i\u0000n\u0000t\u0000r\u0000i\u0000c\u0000a\u0000t\u0000e\u0000,\u0000 \u0000h\u0000y\u0000p\u0000e\u0000r\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000e\u0000d\u0000,\u0000 \u0000p\u0000r\u0000o\u0000f\u0000e\u0000s\u0000s\u0000i\u0000o\u0000n\u0000a\u0000l\u0000 \u0000p\u0000h\u0000o\u0000t\u0000o\u0000g\u0000r\u0000a\u0000p\u0000h\u0000y\u0000,\u0000 \u0000b\u0000o\u0000k\u0000e\u0000h\u0000,\u0000 \u0000h\u0000i\u0000g\u0000h\u0000 \u0000r\u0000e\u0000s\u0000o\u0000l\u0000u\u0000t\u0000i\u0000o\u0000n\u0000,\u0000 \u0000s\u0000h\u0000a\u0000r\u0000p\u0000 \u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000b\u0000e\u0000s\u0000t\u0000 \u0000q\u0000u\u0000a\u0000l\u0000i\u0000t\u0000y\u0000,\u0000 \u0000w\u0000o\u0000m\u0000a\u0000n\u0000,\u0000 \u0000l\u0000o\u0000n\u0000g\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000w\u0000h\u0000i\u0000t\u0000e\u0000 \u0000h\u0000a\u0000i\u0000r\u0000,\u0000 \u0000b\u0000r\u0000a\u0000i\u0000d\u0000,\u0000 \u0000h\u0000a\u0000i\u0000r\u0000 \u0000o\u0000v\u0000e\u0000r\u0000 \u0000o\u0000n\u0000e\u0000 \u0000e\u0000y\u0000e\u0000,\u0000 \u0000b\u0000r\u0000a\u0000i\u0000d\u0000e\u0000d\u0000 \u0000p\u0000o\u0000n\u0000y\u0000t\u0000a\u0000i\u0000l\u0000,\u0000 \u0000p\u0000u\u0000r\u0000p\u0000l\u0000e\u0000 \u0000e\u0000y\u0000e\u0000s\u0000,\u0000 \u0000b\u0000l\u0000a\u0000c\u0000k\u0000 \u0000d\u0000r\u0000e\u0000s\u0000s\u0000,\u0000 \u0000l\u0000o\u0000n\u0000g\u0000 \u0000s\u0000l\u0000e\u0000e\u0000v\u0000e\u0000s\u0000,\u0000 \u0000p\u0000u\u0000f\u0000f\u0000y\u0000 \u0000s\u0000l\u0000e\u0000e\u0000v\u0000e\u0000s\u0000,\u0000 \u0000t\u0000u\u0000r\u0000t\u0000l\u0000e\u0000n\u0000e\u0000c\u0000k\u0000 \u0000d\u0000r\u0000e\u0000s\u0000s\u0000,\u0000 \u0000w\u0000i\u0000d\u0000e\u0000 \u0000l\u0000e\u0000g\u0000 \u0000j\u0000u\u0000m\u0000p\u0000s\u0000u\u0000i\u0000t\u0000 \u0000p\u0000a\u0000n\u0000t\u0000s\u0000,\u0000 \u0000p\u0000a\u0000n\u0000t\u0000s\u0000 \u0000t\u0000u\u0000c\u0000k\u0000e\u0000d\u0000 \u0000i\u0000n\u0000,\u0000 \u0000 \u0000a\u0000M\u0000e\u0000i\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000G\u0000o\u0000o\u0000d\u0000H\u0000a\u0000n\u0000d\u0000s\u0000-\u0000b\u0000e\u0000t\u0000a\u00002\u0000:\u00000\u0000.\u00004\u0000>\u0000,\u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000d\u0000e\u0000t\u0000a\u0000i\u0000l\u0000_\u0000s\u0000l\u0000i\u0000d\u0000e\u0000r\u0000_\u0000v\u00004\u0000:\u00000\u0000.\u00008\u0000>\u0000 \u0000,\u0000 \u0000d\u0000y\u0000n\u0000a\u0000m\u0000i\u0000c\u0000 \u0000p\u0000o\u0000s\u0000e\u0000,\u0000 \u0000(\u0000o\u0000n\u0000e\u0000 \u0000h\u0000a\u0000n\u0000d\u0000 \u0000o\u0000n\u0000 \u0000h\u0000e\u0000r\u0000 \u0000h\u0000i\u0000p\u0000,\u0000 \u0000o\u0000n\u0000e\u0000 \u0000h\u0000a\u0000n\u0000d\u0000 \u0000b\u0000e\u0000h\u0000i\u0000n\u0000d\u0000 \u0000h\u0000e\u0000r\u0000 \u0000h\u0000e\u0000a\u0000d\u0000)\u0000,\u0000 \u0000 \u0000<\u0000l\u0000o\u0000r\u0000a\u0000:\u0000M\u0000e\u0000i\u0000 \u0000M\u0000e\u0000i\u0000-\u00000\u00000\u00000\u00000\u00000\u00003\u0000:\u00000\u0000.\u00008\u0000>\u0000 \u0000,\u0000 \u0000a\u0000b\u0000a\u0000n\u0000d\u0000o\u0000n\u0000e\u0000d\u0000 \u0000b\u0000u\u0000i\u0000l\u0000d\u0000i\u0000n\u0000g\u0000,\u0000 \u0000d\u0000e\u0000s\u0000t\u0000r\u0000u\u0000c\u0000t\u0000i\u0000o\u0000n\u0000,\u0000 \u0000(\u0000m\u0000i\u0000s\u0000t\u0000)\u0000,\u0000 \u0000(\u0000f\u0000o\u0000g\u0000:\u00001\u0000.\u00005\u0000)\u0000,\u0000 \u0000i\u0000n\u0000t\u0000e\u0000r\u0000i\u0000o\u0000r\u0000,\u0000 \u0000(\u0000h\u0000a\u0000l\u0000l\u0000w\u0000a\u0000y\u0000)\u0000,\u0000 \u0000h\u0000a\u0000u\u0000n\u0000t\u0000e\u0000d\u0000,\u0000"
image = pipe(prompt).images[0]

Notebooks
Google Colab
Kaggle
Local Apps
Draw Things
DiffusionBee

Mei Mei

Prompt

UNICODEphotorealistic, (4k), depth of field, (Masterpiece), (realistic skin texture), extremely detailed, intricate, hyper detailed, professional photography, bokeh, high resolution, sharp detail, best quality, woman, long hair, white hair, braid, hair over one eye, braided ponytail, purple eyes, black dress, long sleeves, puffy sleeves, turtleneck dress, wide leg jumpsuit pants, pants tucked in, aMei, <lora:GoodHands-beta2:0.4>, <lora:detail_slider_v4:0.8> , dynamic pose, (one hand on her hip, one hand behind her head), <lora:Mei Mei-000003:0.8> , abandoned building, destruction, (mist), (fog:1.5), interior, (hallway), haunted,

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.

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Model tree for Arczisan/meimei

Base model

runwayml/stable-diffusion-v1-5

Adapter

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