Installation

We recommend Python 3.10+, PyTorch 1.4.0+, and transformers v4.41.0+.

Install with pip

Verify the installation

Once the isntallation is done, verify the installation by:

import ontoaligner

print(ontoaligner.__version__)

From PyPI

OntoAligner is available on the Python Package Index at pypi.org for installation.

pip install -U OntoAligner

From GitHub

The following pip install will installs the latest version of OntoAligner from the main branch of the OntoAligner at GitHub using pip.

pip install git+https://github.com/sciknoworg/OntoAligner.git

Install from Source

You can install OntoAligner directly from source to take advantage of the bleeding edge main branch for development.

1. Clone the repository:

git clone https://github.com/sciknoworg/OntoAligner.git
cd OntoAligner

2. (Optional but recommended) Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies and the library

pip install -e .

Hint

The -e flag installs the package in editable mode, which is ideal for development—changes in the code reflect immediately.

Install PyTorch with CUDA support

To use a GPU/CUDA for aligner models, you must install PyTorch with CUDA support. Follow PyTorch - Get Started for installation steps. We recommend also installing the PEFT library if you plan to perform parameter-efficient fine-tuning or run inference with models fine-tuned using PEFT.