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[docs] Install #12026

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Expand Up @@ -12,183 +12,156 @@ specific language governing permissions and limitations under the License.

# Installation

🤗 Diffusers is tested on Python 3.8+, PyTorch 1.7.0+, and Flax. Follow the installation instructions below for the deep learning library you are using:
Diffusers is tested on Python 3.8+, PyTorch 1.4+, and Flax 0.4.1+. Follow the installation instructions for the deep learning library you're using, [PyTorch](https://pytorch.org/get-started/locally/) or [Flax](https://flax.readthedocs.io/en/latest/).
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@DN6 should we do PyTorch 2.0 or greater here? We have been planning it for a while.

- [PyTorch](https://pytorch.org/get-started/locally/) installation instructions
- [Flax](https://flax.readthedocs.io/en/latest/) installation instructions

## 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.

Create a virtual environment with Python or [uv](https://docs.astral.sh/uv/) (refer to [Installation](https://docs.astral.sh/uv/getting-started/installation/) for installation instructions), a fast Rust-based Python package and project manager.

<hfoptions id="install">
<hfoption id="uv">
Create a [virtual environment](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) for easier management of separate projects and to avoid compatibility issues between dependencies. Use [uv](https://docs.astral.sh/uv/), a Rust-based Python package and project manager, to create a virtual environment and install Diffusers.

```bash
uv venv my-env
source my-env/bin/activate
```

</hfoption>
<hfoption id="Python">

```bash
python -m venv my-env
source my-env/bin/activate
```

</hfoption>
</hfoptions>

You should also install 🤗 Transformers because 🤗 Diffusers relies on its models.

Install Diffusers with one of the following methods.

<frameworkcontent>
<pt>

PyTorch only supports Python 3.8 - 3.11 on Windows. Install Diffusers with uv.

```bash
uv install diffusers["torch"] transformers
```
<hfoptions id="install">
<hfoption id="pip">

You can also install Diffusers with pip.
PyTorch only supports Python 3.8 - 3.11 on Windows.

```bash
pip install diffusers["torch"] transformers
uv pip install diffusers["torch"] transformers
```

</pt>
<jax>

Install Diffusers with uv.
Use the command below for Flax.

```bash
uv pip install diffusers["flax"] transformers
```

You can also install Diffusers with pip.

```bash
pip install diffusers["flax"] transformers
```

</jax>
</frameworkcontent>

## Install with conda

After activating your virtual environment, with `conda` (maintained by the community):
</hfoption>
<hfoption id="conda">

```bash
conda install -c conda-forge diffusers
```

## Install from source
</hfoption>
<hfoption id="source">

Before installing 🤗 Diffusers from source, make sure you have PyTorch and 🤗 Accelerate installed.
A source install installs the `main` version instead of the latest `stable` version. The `main` version is useful for staying updated with the latest changes but it may not always be stable. If you run into a problem, open an [Issue](https://github.com/huggingface/diffusers/issues/new/choose) and we will try to resolve it as soon as possible.

To install 🤗 Accelerate:
Make sure [Accelerate](https://huggingface.co/docs/accelerate/index) is installed.

```bash
pip install accelerate
uv pip install accelerate
```

Then install 🤗 Diffusers from source:
Install Diffusers from source with the command below.

```bash
pip install git+https://github.com/huggingface/diffusers
uv 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/diffusers/issues/new/choose) so we can fix it even sooner!
</hfoption>
</hfoptions>

## Editable install

You will need an editable install if you'd like to:
An editable install is recommended for development workflows or if you're using the `main` version of the source code. A special link is created between the cloned repository and the Python library paths. This avoids reinstalling a package after every change.

* 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.

Clone the repository and install 🤗 Diffusers with the following commands:
<hfoptions id="editable">
<hfoption id="PyTorch">

```bash
git clone https://github.com/huggingface/diffusers.git
cd diffusers
uv pip install -e ".[torch]"
```

<frameworkcontent>
<pt>
```bash
pip install -e ".[torch]"
```
</pt>
<jax>
</hfoption>
<hfoption id="Flax">

```bash
pip install -e ".[flax]"
git clone https://github.com/huggingface/diffusers.git
cd diffusers
uv pip install -e ".[flax]"
```
</jax>
</frameworkcontent>

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/python3.10/site-packages/`, Python will also search the `~/diffusers/` folder you cloned to.

<Tip warning={true}>

You must keep the `diffusers` folder if you want to keep using the library.
</hfoption>
</hfoptions>

</Tip>
> [!WARNING]
> You must keep the `diffusers` folder if you want to keep using the library with the editable install.

Now you can easily update your clone to the latest version of 🤗 Diffusers with the following command:
Update your cloned repository to the latest version of Diffusers with the command below.

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

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

## Cache

Model weights and files are downloaded from the Hub to a cache which is usually your home directory. You can change the cache location by specifying the `HF_HOME` or `HUGGINFACE_HUB_CACHE` environment variables or configuring the `cache_dir` parameter in methods like [`~DiffusionPipeline.from_pretrained`].
Model weights and files are downloaded from the Hub to a cache, which is usually your home directory. Change the cache location with the [HF_HOME](https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhome) or [HF_HUB_CACHE](https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhubcache) environment variables or configuring the `cache_dir` parameter in methods like [`~DiffusionPipeline.from_pretrained`].

Cached files allow you to run 🤗 Diffusers offline. To prevent 🤗 Diffusers from connecting to the internet, set the `HF_HUB_OFFLINE` environment variable to `1` and 🤗 Diffusers will only load previously downloaded files in the cache.
<hfoptions id="cache">
<hfoption id="env variable">

```bash
export HF_HOME="/path/to/your/cache"
export HF_HUB_CACHE="/path/to/your/hub/cache"
```

</hfoption>
<hfoption id="from_pretrained">

```py
from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
cache_dir="/path/to/your/cache"
)
```

</hfoption>
</hfoptions>

Cached files allow you to use Diffusers offline. Set the [HF_HUB_OFFLINE](https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhuboffline) environment variable to `1` to prevent Diffusers from connecting to the internet.

```shell
export HF_HUB_OFFLINE=1
```

For more details about managing and cleaning the cache, take a look at the [caching](https://huggingface.co/docs/huggingface_hub/guides/manage-cache) guide.
For more details about managing and cleaning the cache, take a look at the [Understand caching](https://huggingface.co/docs/huggingface_hub/guides/manage-cache) guide.

## Telemetry logging

Our library gathers telemetry information during [`~DiffusionPipeline.from_pretrained`] requests.
The data gathered includes the version of 🤗 Diffusers and PyTorch/Flax, the requested model or pipeline class,
and the path to a pretrained checkpoint if it is hosted on the Hugging Face Hub.
Diffusers gathers telemetry information during [`~DiffusionPipeline.from_pretrained`] requests.
The data gathered includes the Diffusers and PyTorch/Flax version, the requested model or pipeline class,
and the path to a pretrained checkpoint if it is hosted on the Hub.

This usage data helps us debug issues and prioritize new features.
Telemetry is only sent when loading models and pipelines from the Hub,
and it is not collected if you're loading local files.

We understand that not everyone wants to share additional information,and we respect your privacy.
You can disable telemetry collection by setting the `HF_HUB_DISABLE_TELEMETRY` environment variable from your terminal:
Opt-out and disable telemetry collection with the [HF_HUB_DISABLE_TELEMETRY](https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhubdisabletelemetry) environment variable.

On Linux/MacOS:
<hfoptions id="telemetry">
<hfoption id="Linux/macOS">

```bash
export HF_HUB_DISABLE_TELEMETRY=1
```

On Windows:
</hfoption>
<hfoption id="Windows">

```bash
set HF_HUB_DISABLE_TELEMETRY=1
```

</hfoption>
</hfoptions>