language:
- en
tags:
- stable-diffusion
- text-to-image
license: bigscience-bloom-rail-1.0
inference: false
waifu-diffusion - Diffusion for Weebs
waifu-diffusion is a latent text-to-image diffusion model that has been conditioned on high-quality anime images through fine-tuning on high quality anime images.
Model Description
The model used for fine-tuning is Stable Diffusion V1-4, which is a latent text-to-image diffusion model trained on LAION2B-en.
The current model is fine-tuned from 56 thousand images from Danbooru selected with an aesthetic score greater than 6.0.
With Textual Inversion, the embeddings for the text encoder has been trained to align more with anime-styled images, reducing excessive prompting.
Training Data & Annotative Prompting
The data used for fine-tuning has come from a random sample of 56k Danbooru images, which were filtered based on CLIP Aesthetic Scoring where only images with an aesthetic score greater than 6.0 were used.
Downstream Uses
This model can be used for entertainment purposes and as a generative art assistant. The EMA model can be used for additional fine-tuning.
Example Code
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
model_id = "hakurei/waifu-diffusion"
device = "cuda"
pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=True)
pipe = pipe.to(device)
prompt = "a photo of reimu hakurei. anime style"
with autocast("cuda"):
image = pipe(prompt, guidance_scale=7.5)["sample"][0]
image.save("reimu_hakurei.png")
Team Members and Acknowledgements
This project would not have been possible without the incredible work by the CompVis Researchers.