Installation — Sentence Transformers documentation (original) (raw)
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.
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
Default
uv pip install -U sentence-transformers
Image
uv pip install -U "sentence-transformers[image]"
Audio
uv pip install -U "sentence-transformers[audio]"
Video
uv pip install -U "sentence-transformers[video]"
Training
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):
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.
ONNX
For GPU and CPU:
uv pip install -U "sentence-transformers[onnx-gpu]"
For CPU only:
uv pip install -U "sentence-transformers[onnx]"
OpenVINO
uv pip install -U "sentence-transformers[openvino]"
Development
uv pip install -U "sentence-transformers[dev]"
Install with pip
Default
pip install -U sentence-transformers
Image
pip install -U "sentence-transformers[image]"
Audio
pip install -U "sentence-transformers[audio]"
Video
pip install -U "sentence-transformers[video]"
Training
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):
And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):
Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.
ONNX
For GPU and CPU:
pip install -U "sentence-transformers[onnx-gpu]"
For CPU only:
pip install -U "sentence-transformers[onnx]"
OpenVINO
pip install -U "sentence-transformers[openvino]"
Development
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.
Default
conda install -c conda-forge sentence-transformers
Image
pip install -U "sentence-transformers[image]"
Audio
pip install -U "sentence-transformers[audio]"
Video
pip install -U "sentence-transformers[video]"
Training
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):
And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):
Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.
ONNX
For GPU and CPU:
pip install -U "sentence-transformers[onnx-gpu]"
For CPU only:
pip install -U "sentence-transformers[onnx]"
OpenVINO
pip install -U "sentence-transformers[openvino]"
Development
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:
Default
pip install git+https://github.com/huggingface/sentence-transformers.git
Image
pip install -U "sentence-transformers[image] @ git+https://github.com/huggingface/sentence-transformers.git"
Audio
pip install -U "sentence-transformers[audio] @ git+https://github.com/huggingface/sentence-transformers.git"
Video
pip install -U "sentence-transformers[video] @ git+https://github.com/huggingface/sentence-transformers.git"
Training
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):
And to track your carbon emissions while training and have this information automatically included in your model cards, also install codecarbon (recommended):
Don’t forget to add the module names to report_to in the Training Arguments when training, or they will not be used.
ONNX
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"
OpenVINO
pip install -U "sentence-transformers[openvino] @ git+https://github.com/huggingface/sentence-transformers.git"
Development
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.