MykosX/the-glowing-anime-mix-xl

The glowing anime mix xl

MykosX/the-glowing-anime-mix-xl is a Stable Diffusion model that can be used both for:

• text-to-image: generates decent images, the lighting effect may get annoying
• image-to-image: seems to improve images generated by this model, great results when using images with some degree of structure (something really worth improving)

Image show-case

	(seed=300)**	(seed=400)**	(seed=500)**
text-to-image
image-to-image

	(seed=300)**	(seed=400)**	(seed=500)**
text-to-image
image-to-image

Base image (from another model)	image-to-image (seed=300)**	image-to-image (seed=400)**	image-to-image (seed=500)**
Base image (from another model)	image-to-image (seed=300)*	image-to-image (seed=400)*	image-to-image (seed=500)*

** using these defaults unless specified:

Setting	Default value
prompt (landscape)	landscape image, a boy and girl having fun on the beach
prompt (portrait)	portrait image, a girl in a nice dress posing for a photo
negative prompt	deformed iris, deformed pupils, bad anatomy, cloned face, extra arms, extra legs, missing fingers, too many fingers
size (landscape)	1024 x 768
size (portrait)	768 x 1024
seed	300
guidance scale	12.0
strength	0.5
inference steps	30

Diffusers

For more general information on how to run text-to-image models with 🧨 Diffusers, see the docs.

1. Installation

pip install diffusers transformers accelerate

2. Running example for text-to-image generation

import torch

from   diffusers import AutoPipelineForText2Image

pipe = AutoPipelineForText2Image.from_pretrained('MykosX/the-glowing-anime-mix-xl', torch_dtype=torch.float32)
pipe = pipe.to("cpu")

prompt = "portrait image, a girl in a nice dress posing for a photo"

image = pipe(prompt).images[0]  
image.save("./images/text-to-image.png")

3. Running example for image-to-image generation

import torch

from   diffusers import AutoPipelineForImage2Image
from   PIL       import Image

pipe = AutoPipelineForImage2Image.from_pretrained('MykosX/the-glowing-anime-mix-xl', torch_dtype=torch.float32)
pipe = pipe.to("cpu")

base_image = Image.open("./images/text-to-image/girl-posing-photo-(original).jpg")
prompt = "portrait image, a girl in a nice dress posing for a photo"

image = pipe(prompt, image=base_image).images[0]  
image.save("./images/image-to-image.png")

PS

Play with the model and don't hesitate to show off