[community] Load Models from Sources like Civitai into Existing Pipelines

examples/model_search/README.md

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+# Search models on Civitai and Hugging Face
+
+The [auto_diffusers](https://github.com/suzukimain/auto_diffusers) library provides additional functionalities to Diffusers such as searching for models on Civitai and the Hugging Face Hub.
+Please refer to the original library [here](https://pypi.org/project/auto-diffusers/)
+
+## Installation
+
+Before running the scripts, make sure to install the library's training dependencies:
+
+> [!IMPORTANT]
+> To make sure you can successfully run the latest versions of the example scripts, we highly recommend **installing from source** and keeping the installation up to date as we update the example scripts frequently and install some example-specific requirements. To do this, execute the following steps in a new virtual environment.
+
+```bash
+git clone https://github.com/huggingface/diffusers
+cd diffusers
+pip install .
+```bash
+!wget https://raw.githubusercontent.com/suzukimain/auto_diffusers/refs/heads/master/src/auto_diffusers/pipeline_easy.py
+```
+
+### Search for Civitai
+```python
+from pipeline_easy import (
+    EasyPipelineForText2Image,
+    EasyPipelineForImage2Image,
+    EasyPipelineForInpainting,
+)
+
+# Text-to-Image
+pipeline = EasyPipelineForText2Image.from_civitai(
+    "search_word",
+    base_model="SD 1.5",
+).to("cuda")
+
+
+# Image-to-Image
+pipeline = EasyPipelineForImage2Image.from_civitai(
+    "search_word",
+    base_model="SD 1.5",
+).to("cuda")
+
+
+# Inpainting
+pipeline = EasyPipelineForInpainting.from_civitai(
+    "search_word",
+    base_model="SD 1.5",
+).to("cuda")
+```
+
+### Search for Hugging Face
+```python
+from pipeline_easy import (
+    EasyPipelineForText2Image,
+    EasyPipelineForImage2Image,
+    EasyPipelineForInpainting,
+)
+
+# Text-to-Image
+pipeline = EasyPipelineForText2Image.from_huggingface(
+    "search_word",
+    checkpoint_format="diffusers",
+).to("cuda")
+
+
+# Image-to-Image
+pipeline = EasyPipelineForImage2Image.from_huggingface(
+    "search_word",
+    checkpoint_format="diffusers",
+).to("cuda")
+
+
+# Inpainting
+pipeline = EasyPipelineForInpainting.from_huggingface(
+    "search_word",
+    checkpoint_format="diffusers",
+).to("cuda")
+```
+
+
+### Application Examples
+
+```python
+from pipeline_easy import (
+    search_huggingface,
+    search_civitai,
+) 
+
+# Search Lora
+Lora = search_civitai(
+    "Keyword_to_search_Lora",
+    model_type="LORA",
+    base_model = "SD 1.5",
+    download=True,
+    )
+# Load Lora into the pipeline.
+pipeline.load_lora_weights(Lora)
+
+
+# Search TextualInversion
+TextualInversion = search_civitai(
+    "EasyNegative",
+    model_type="TextualInversion",
+    base_model = "SD 1.5",
+    download=True
+)
+# Load TextualInversion into the pipeline.
+pipeline.load_textual_inversion(TextualInversion, token="EasyNegative")
+```
+
+> [!TIP]
+> **If an error occurs, insert the `token` and run again.**
+
+### `EasyPipeline.from_civitai` parameters
+
+| Name            | 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.  <br>(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` parameters
+
+| Name            | 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. <br>(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.                                             |
+
+
+### `EasyPipeline.from_huggingface` parameters
+
+| Name                  | 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.<br>● `single_file` to search for `single file checkpoint` <br>●`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` parameters
+
+| Name                  | 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. <br>● `single_file` to search for `single file checkpoint` <br>●`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.                           |