CONTENTS

• About The Project
• How to use
• Search Hubs
  • Search Civitai
  • Search Huggingface
• License
• Acknowledgement

About The Project

Enhance the functionality of diffusers.

• Search models from Hugging Face and Civitai.
• Officially listed in the Hugging Face Diffusers Community Projects documentation.

Image of the listing location on Hugging Face

Regarding the Civitai API bug

The previously reported Civitai API issue has largely been resolved.

Previous issue description

Due to recent specification changes in the Civitai API, we were aware of the following issues:

• Reduced search accuracy
• Some search results not being returned

A temporary workaround has been implemented for the above issues, but since certain search results are still not returned, there is a possibility that some models may not be found.

link： civitai/civitai#1757

How to use

pip install --quiet auto_diffusers

import torch
from auto_diffusers import EasyPipelineForText2Image

# Load an official Hugging Face model
pipe = EasyPipelineForText2Image.from_huggingface(
    "stabilityai/stable-diffusion-xl-base-1.0",
    dtype=torch.float16,
).to("cuda")
img = pipe("cat").images[0]
img.save("cat.png")


# Search for Civitai
pipe = EasyPipelineForText2Image.from_civitai(
    "search_word",
    dtype=torch.float16,
).to("cuda")
image = pipe("cat").images[0]
image.save("cat.png")

Use dtype for new code. torch_dtype remains supported for compatibility, but do not pass both arguments at the same time.

Search Civitai and Huggingface

# Load Lora into the pipeline.
pipe.auto_load_lora_weights("Detail Tweaker")

# Load TextualInversion into the pipeline.
pipe.auto_load_textual_inversion("EasyNegative", token="EasyNegative")

Search Civitai

Tip

If an error occurs, insert the token and run again.

EasyPipeline.from_civitai parameters

Name	Type	Default	Description
search_word	string, Path	required	The search query string. Can be a keyword, Civitai URL, local directory or file path.
model_type	string	Checkpoint	The type of model to search for. (for example Checkpoint, TextualInversion, Controlnet, LORA, Hypernetwork, AestheticGradient, Poses)
base_model	string	None	Trained model tag (for example SD 1.5, SD 3.5, SDXL 1.0)
dtype	string, torch.dtype	None	Override the default torch.dtype and load the model with another dtype.
force_download	bool	False	Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.
cache_dir	string, Path	None	Path to the folder where cached files are stored.
resume	bool	False	Whether to resume an incomplete download.
token	string	None	API token for Civitai authentication.

search_civitai parameters

Name	Type	Default	Description
search_word	string, Path	required	The search query string. Can be a keyword, Civitai URL, local directory or file path.
model_type	string	Checkpoint	The type of model to search for. (for example Checkpoint, TextualInversion, Controlnet, LORA, Hypernetwork, AestheticGradient, Poses)
base_model	string	None	Trained model tag (for example SD 1.5, SD 3.5, SDXL 1.0)
download	bool	False	Whether to download the model.
force_download	bool	False	Whether to force the download if the model already exists.
cache_dir	string, Path	None	Path to the folder where cached files are stored.
resume	bool	False	Whether to resume an incomplete download.
token	string	None	API token for Civitai authentication.
include_params	bool	False	Whether to include parameters in the returned data.
skip_error	bool	False	Whether to skip errors and return None.

Search Huggingface

Tip

If an error occurs, insert the token and run again.

EasyPipeline.from_huggingface parameters

Name	Type	Default	Description
search_word	string, Path	required	The search query string. Can be a keyword, Hugging Face URL, local directory or file path, or a Hugging Face path (<creator>/<repo>).
checkpoint_format	string	single_file	The format of the model checkpoint. - single_file to search for single file checkpoint - diffusers to search for multifolder diffusers format checkpoint
dtype	string, torch.dtype	None	Override the default torch.dtype and load the model with another dtype.
force_download	bool	False	Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.
cache_dir	string, Path	None	Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not used.
token	string, bool	None	The token to use as HTTP bearer authorization for remote files.

search_huggingface parameters

Name	Type	Default	Description
search_word	string, Path	required	The search query string. Can be a keyword, Hugging Face URL, local directory or file path, or a Hugging Face path (<creator>/<repo>).
checkpoint_format	string	single_file	The format of the model checkpoint. - single_file to search for single file checkpoint - diffusers to search for multifolder diffusers format checkpoint
pipeline_tag	string	None	Tag to filter models by pipeline.
download	bool	False	Whether to download the model.
force_download	bool	False	Whether or not to force the (re-)download of the model weights and configuration files, overriding the cached versions if they exist.
cache_dir	string, Path	None	Path to a directory where a downloaded pretrained model configuration is cached if the standard cache is not used.
token	string, bool	None	The token to use as HTTP bearer authorization for remote files.
include_params	bool	False	Whether to include parameters in the returned data.
skip_error	bool	False	Whether to skip errors and return None.

License

In accordance with Apache-2.0 license

Acknowledgement

I have used open source resources and free tools in the creation of this project.

I would like to take this opportunity to thank the open source community and those who provided free tools.