Installation

We recommend Python 3.10+, PyTorch 1.11.0+, and transformers v4.41.0+. There are several extra options to install Sentence Transformers:

  • Default: Allows loading, saving, and inference (i.e., getting embeddings) of text models.

  • Image: Adds dependencies for models that process images (e.g., CLIP, VLM-based models).

  • Audio: Adds dependencies for models that process audio inputs.

  • Video: Adds dependencies for models that process video inputs.

  • Training: Adds dependencies for training and finetuning models.

  • ONNX: Adds dependencies for loading, saving, inference, optimizing, and quantizing of models using the ONNX backend.

  • OpenVINO: Adds dependencies for loading, saving, and inference of models using the OpenVINO backend.

  • Development: All of the above plus some dependencies for developing Sentence Transformers, see Editable Install.

To pass torchcodec.AudioDecoder or torchcodec.VideoDecoder instances as inputs, you must install torchcodec separately, e.g. with: pip install torchcodec.
Note that you can mix and match the various extras, e.g. pip install -U "sentence-transformers[train,image,video,onnx-gpu]".

Install with uv

uv pip install -U sentence-transformers

uv pip install -U "sentence-transformers[image]"

uv pip install -U "sentence-transformers[audio]"

uv pip install -U "sentence-transformers[video]"

uv pip install -U "sentence-transformers[train]"

To use Weights and Biases or Trackio to track your training logs, you should also install wandb or trackio (recommended):

uv pip install trackio

And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):

uv pip install codecarbon

Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.

For GPU and CPU:

uv pip install -U "sentence-transformers[onnx-gpu]"

For CPU only:

uv pip install -U "sentence-transformers[onnx]"

uv pip install -U "sentence-transformers[openvino]"

uv pip install -U "sentence-transformers[dev]"

Install with pip

pip install -U sentence-transformers

pip install -U "sentence-transformers[image]"

pip install -U "sentence-transformers[audio]"

pip install -U "sentence-transformers[video]"

pip install -U "sentence-transformers[train]"

To use Weights and Biases or Trackio to track your training logs, you should also install wandb or trackio (recommended):

pip install trackio

And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):

pip install codecarbon

Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.

For GPU and CPU:

pip install -U "sentence-transformers[onnx-gpu]"

For CPU only:

pip install -U "sentence-transformers[onnx]"

pip install -U "sentence-transformers[openvino]"

pip install -U "sentence-transformers[dev]"

Install with Conda

The base package is available on conda-forge. Extras (e.g. [image], [train]) are a pip concept and not available via conda, so they are installed with pip.

conda install -c conda-forge sentence-transformers

pip install -U "sentence-transformers[image]"

pip install -U "sentence-transformers[audio]"

pip install -U "sentence-transformers[video]"

conda install -c conda-forge sentence-transformers accelerate datasets

To use Weights and Biases or Trackio to track your training logs, you should also install wandb or trackio (recommended):

pip install trackio

And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):

pip install codecarbon

Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.

For GPU and CPU:

pip install -U "sentence-transformers[onnx-gpu]"

For CPU only:

pip install -U "sentence-transformers[onnx]"

pip install -U "sentence-transformers[openvino]"

conda install -c conda-forge sentence-transformers accelerate datasets pre-commit pytest ruff

Install from Source

You can install sentence-transformers directly from source to take advantage of the bleeding edge main branch rather than the latest stable release:

pip install git+https://github.com/huggingface/sentence-transformers.git

pip install -U "sentence-transformers[image] @ git+https://github.com/huggingface/sentence-transformers.git"

pip install -U "sentence-transformers[audio] @ git+https://github.com/huggingface/sentence-transformers.git"

pip install -U "sentence-transformers[video] @ git+https://github.com/huggingface/sentence-transformers.git"

pip install -U "sentence-transformers[train] @ git+https://github.com/huggingface/sentence-transformers.git"

To use Weights and Biases or Trackio to track your training logs, you should also install wandb or trackio (recommended):

pip install trackio

And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):

pip install codecarbon

Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.

For GPU and CPU:

pip install -U "sentence-transformers[onnx-gpu] @ git+https://github.com/huggingface/sentence-transformers.git"

For CPU only:

pip install -U "sentence-transformers[onnx] @ git+https://github.com/huggingface/sentence-transformers.git"

pip install -U "sentence-transformers[openvino] @ git+https://github.com/huggingface/sentence-transformers.git"

pip install -U "sentence-transformers[dev] @ git+https://github.com/huggingface/sentence-transformers.git"

Editable Install

If you want to make changes to sentence-transformers, you will need an editable install. Clone the repository and install it with these commands:

git clone https://github.com/huggingface/sentence-transformers
cd sentence-transformers
pip install -e ".[train,dev]"

These commands will link the new sentence-transformers folder and your Python library paths, such that this folder will be used when importing sentence-transformers.

Install PyTorch with CUDA support

To use a GPU/CUDA, you must install PyTorch with CUDA support. Follow PyTorch - Get Started for installation steps.