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CONTENTS
pipeline.auto_load_lora_weights()
and pipeline.auto_load_textual_inversion()
may not work properly at the moment due to a bug in the Civitai API.
Enhance the functionality of diffusers.
pip install --quiet auto_diffusers
from auto_diffusers import EasyPipelineForText2Image
# Search for Huggingface
pipe = EasyPipelineForText2Image.from_huggingface("search_word").to("cuda")
img = pipe("cat").images[0]
img.save("cat.png")
# Search for Civitai
pipe = EasyPipelineForText2Image.from_civitai("search_word").to("cuda")
image = pipe("cat").images[0]
image.save("cat.png")
# 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")
[!TIP] If an error occurs, insert the
token
and run again.
EasyPipeline.from_civitai
parametersName | Type | Default | Description |
---|---|---|---|
search_word | string, Path | ー | 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 ) |
torch_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
parametersName | Type | Default | Description |
---|---|---|---|
search_word | string, Path | ー | 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. |
[!TIP] If an error occurs, insert the
token
and run again.
EasyPipeline.from_huggingface
parametersName | Type | Default | Description |
---|---|---|---|
search_word | string, Path | ー | 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 |
torch_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
parametersName | Type | Default | Description |
---|---|---|---|
search_word | string, Path | ー | 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. |
In accordance with Apache-2.0 license
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.
FAQs
diffusers with search engine
We found that auto-diffusers demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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