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<p align="center">
    <br>
    <img src="https://raw.githubusercontent.com/huggingface/diffusers/77aadfee6a891ab9fcfb780f87c693f7a5beeb8e/docs/source/imgs/diffusers_library.jpg" width="400"/>
    <br>
</p>

# 🧨 Diffusers


🤗 Diffusers provides pretrained diffusion models across multiple modalities, such as vision and audio, and serves
as a modular toolbox for inference and training of diffusion models.

More precisely, 🤗 Diffusers offers:

- State-of-the-art diffusion pipelines that can be run in inference with just a couple of lines of code (see [src/diffusers/pipelines](https://github.com/huggingface/diffusers/tree/main/src/diffusers/pipelines)).
- Various noise schedulers that can be used interchangeably for the prefered speed vs. quality trade-off in inference (see [src/diffusers/schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers)).
- Multiple types of models, such as UNet, that can be used as building blocks in an end-to-end diffusion system (see [src/diffusers/models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models)).
- Training examples to show how to train the most popular diffusion models (see [examples](https://github.com/huggingface/diffusers/tree/main/examples)).

# Installation

Install Diffusers for with PyTorch. Support for other libraries will come in the future

🤗 Diffusers is tested on Python 3.6+, and PyTorch 1.4.0+.

## Install with pip

You should install 🤗 Diffusers in a [virtual environment](https://docs.python.org/3/library/venv.html).
If you're unfamiliar with Python virtual environments, take a look at this [guide](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
A virtual environment makes it easier to manage different projects, and avoid compatibility issues between dependencies.

Start by creating a virtual environment in your project directory:

```bash
python -m venv .env
```

Activate the virtual environment:

```bash
source .env/bin/activate
```

Now you're ready to install 🤗 Diffusers with the following command:

```bash
pip install diffusers
```

## Install from source

Install 🤗 Diffusers from source with the following command:

```bash
pip install git+https://github.com/huggingface/diffusers
```

This command installs the bleeding edge `main` version rather than the latest `stable` version.
The `main` version is useful for staying up-to-date with the latest developments.
For instance, if a bug has been fixed since the last official release but a new release hasn't been rolled out yet.
However, this means the `main` version may not always be stable.
We strive to keep the `main` version operational, and most issues are usually resolved within a few hours or a day.
If you run into a problem, please open an [Issue](https://github.com/huggingface/transformers/issues) so we can fix it even sooner!

## Editable install

You will need an editable install if you'd like to:

* Use the `main` version of the source code.
* Contribute to 🤗 Diffusers and need to test changes in the code.

Clone the repository and install 🤗 Diffusers with the following commands:

```bash
git clone https://github.com/huggingface/diffusers.git
cd transformers
pip install -e .
```

These commands will link the folder you cloned the repository to and your Python library paths.
Python will now look inside the folder you cloned to in addition to the normal library paths.
For example, if your Python packages are typically installed in `~/anaconda3/envs/main/lib/python3.7/site-packages/`, Python will also search the folder you cloned to: `~/diffusers/`.

<Tip warning={true}>

You must keep the `diffusers` folder if you want to keep using the library.

</Tip>

Now you can easily update your clone to the latest version of 🤗 Diffusers with the following command:

```bash
cd ~/diffusers/
git pull
```

Your Python environment will find the `main` version of 🤗 Diffuers on the next run.

