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
ๅ็จๅฉ็จใซ้ขใใๆฅๆฌ่ชใงใฎๅใๅใใใฏใ[email protected] ใพใงใ้กใ่ดใใพใใ
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 = "ๆด็ฌใใซใฉใใซใขใผใ"
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
ๅ็จๅฉ็จใซ้ขใใๆฅๆฌ่ชใงใฎๅใๅใใใฏใ[email protected] ใพใงใ้กใ่ดใใพใใ
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 โA red cube on top of a blue sphereโ
- 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]. ใใธใในใๅๆฅญใซ้ขใใใๅใๅใใใฏ[email protected]ใซใ้ฃ็ตกใใ ใใใ