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Japanese Stable Diffusion Pokemon Model Card

Stable-Diffusion-Pokemon-ja is a Japanese-specific latent text-to-image diffusion model capable of generating Pokemon images given any text input.

This model was trained by using a powerful text-to-image model, diffusers For more information about our training method, see train_ja_model.py.

Model Details


Firstly, install our package as follows. This package is modified 🤗's Diffusers library to run Japanese Stable Diffusion.

pip install git+https://github.com/rinnakk/japanese-stable-diffusion
sudo apt-get install git-lfs
git clone https://huggingface.co/svjack/Stable-Diffusion-Pokemon-ja

Run this command to log in with your HF Hub token if you haven't before:

huggingface-cli login

Running the pipeline with the LMSDiscreteScheduler scheduler:

from japanese_stable_diffusion import JapaneseStableDiffusionPipeline
import torch

from torch import autocast
from diffusers import LMSDiscreteScheduler

scheduler = LMSDiscreteScheduler(beta_start=0.00085, beta_end=0.012,
     beta_schedule="scaled_linear", num_train_timesteps=1000)

#pretrained_model_name_or_path = "jap_model_26000"

#### sudo apt-get install git-lfs
#### git clone https://huggingface.co/svjack/Stable-Diffusion-Pokemon-ja
pretrained_model_name_or_path = "Stable-Diffusion-Pokemon-ja"

pipe = JapaneseStableDiffusionPipeline.from_pretrained(pretrained_model_name_or_path,
                                                           scheduler=scheduler, use_auth_token=True)

pipe = pipe.to("cuda")

#### disable safety_checker
pipe.safety_checker = lambda images, clip_input: (images, False)

imgs = pipe("鉢植えの植物を頭に載せた漫画のキャラクター",
                    num_inference_steps = 100
image = imgs.images[0]

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