DeepPavlov supports Linux, Windows 10+ (through WSL/WSL2), MacOS (Big Sur+) platforms, Python 3.6-3.10. Depending on the model used, you may need from 4 to 16 GB RAM.
Install with pip¶
You should install DeepPavlov in a virtual environment. If you’re unfamiliar with Python virtual environments, take a look at this guide. A virtual environment makes it easier to manage different projects, and avoid compatibility issues between dependencies.
Create a virtual environment:
python -m venv env
Activate the virtual environment on Linux (source could be replaced with .):
Install DeepPavlov inside this virtual environment:
pip install deeppavlov
Install from source¶
Install DeepPavlov dev branch from source with the following command:
pip install git+http://github.com/deeppavlov/DeepPavlov@dev
This command installs the bleeding edge dev version rather than the latest release version. The dev version is useful for staying up-to-date with the latest developments. For instance, if a bug has been fixed since the last release but a new release hasn’t been rolled out yet. However, this means the dev version may not always be stable.
You will need an editable install if you want to make changes in the DeepPavlov source code that immediately take place without requiring a new installation.
Clone the repository and install DeepPavlov with the following commands:
git clone http://github.com/deeppavlov/DeepPavlov.git pip install -e DeepPavlov
We have built several DeepPavlov based Docker images, which include:
DeepPavlov based Jupyter notebook Docker image;
Docker images which serve some of our models and allow to access them via REST API (riseapi mode).
Here is our DockerHub repository with images and deployment instructions.