metadata

language:
  - ja
tags:
  - text-to-image
  - stable-diffusion
  - japanese-stable-diffusion
pipeline_tag: text-to-image
license: other
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Japanese Stable Diffusion XL

Please note: for commercial usage of this model, please see https://stability.ai/membership

商用利用に関する日本語での問い合わせは　[email protected] までお願い致します。

Model Details

Japanese Stable Diffusion XL (JSDXL) is a Japanese-specific SDXL model that is capable of inputting prompts in Japanese and generating Japanese-style images.

Usage


from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained(
    "stabilityai/japanese-stable-diffusion-xl", trust_remote_code=True
)
pipeline.to("cuda")

# if using torch < 2.0
# pipeline.enable_xformers_memory_efficient_attention()

prompt = "柴犬、カラフルアート"

image = pipeline(prompt=prompt).images[0]

Model Details

Developed by: Stability AI
Model type: Diffusion-based text-to-image generative model
Model Description: This model is a fine-tuned model based on SDXL 1.0. In order to maximize the understanding of the Japanese language and Japanese culture/expressions while preserving the versatility of the pre-trained model, we performed a PEFT training using one Japanese-specific compatible text encoder. As a PEFT method, we applied Orthogonal Fine-tuning (OFT) for better results and training stability.
License: STABILITY AI JAPANESE STABLE DIFFUSION XL COMMUNITY LICENSE

Uses

Direct Use

Commercial use: for commercial usage of this model, please see https://stability.ai/membership

商用利用に関する日本語での問い合わせは　[email protected] までお願い致します。

Research: possible research areas/tasks include:

Generation of artworks and use in design and other artistic processes.
Applications in educational or creative tools.
Research on generative models.
Safe deployment of models which have the potential to generate harmful content.
Probing and understanding the limitations and biases of generative models.

Excluded uses are described below.

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.

Limitations and Bias

Limitations

The model does not achieve perfect photorealism
The model cannot render legible text
The model struggles with more difficult tasks which involve compositionality, such as rendering an image corresponding to “A red cube on top of a blue sphere”
Faces and people in general may not be generated properly.
The autoencoding part of the model is lossy.

Bias

While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.

How to cite

@misc{JSDXL, 
    url    = {[https://huggingface.co/stabilityai/japanese-stable-diffusion-xl](https://huggingface.co/stabilityai/japanese-stable-diffusion-xl)}, 
    title  = {Japanese Stable Diffusion XL}, 
    author = {Shing, Makoto and Akiba, Takuya}
}

Contact

For questions and comments about the model, please join Stable Community Japan.
For future announcements / information about Stability AI models, research, and events, please follow https://twitter.com/StabilityAI_JP.
For business and partnership inquiries, please contact [email protected]. ビジネスや協業に関するお問い合わせは[email protected]にご連絡ください。