metadata
license: cc-by-nc-sa-4.0
tags:
- common-canvas
- stable-diffusion
- sdxl
datasets:
- common-canvas/commoncatalog-cc-by-sa
- common-canvas/commoncatalog-cc-by
- common-canvas/commoncatalog-cc-by-nc-sa
- common-canvas/commoncatalog-cc-by-nc
language:
- en
CommonCanvas-XL-NC 0.1
Specifications
Input: CommonCatalog Text Captions
Output: CommonCatalog Images
Architecture: Stable Diffusion XL
Credit: CommonCanvas, StabilityAI, mosaicML, @multimodalart, @Wauplin, @lhoestq
NSFW: Yes
Text: https://arxiv.org/abs/2310.16825
LICENSE:
This work is licensed under CC BY-NC-SA 4.0
Details
training data : Flickr100M dataset
bias : internet connected Western countries
limitations : text generation, complex composition, faces, non-English languages, VAE
use : research, deployment, examination, art, education, creative use
prohibited : commercial use
suggested training : mosaicML https://github.com/mosaicml/diffusion.
Citation
@article{gokaslan2023commoncanvas,
title={CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images},
author={Gokaslan, Aaron and Cooper, A Feder and Collins, Jasmine and Seguin, Landan and Jacobson, Austin and Patel, Mihir and Frankle, Jonathan and Stephenson, Cory and Kuleshov, Volodymyr},
journal={arXiv preprint arXiv:2310.16825},
year={2023}
}
Code
from diffusers import StableDiffusionXLPipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
"common-canvas/CommonCanvas-XL-NC",
custom_pipeline="multimodalart/sdxl_perturbed_attention_guidance", #read more at https://huggingface.co/multimodalart/sdxl_perturbed_attention_guidance
torch_dtype=torch.float16
).to(device)
prompt = "a cat sitting in a car seat"
image = pipe(prompt, num_inference_steps=25).images[0]