Installation

miniML is written in Python. To use miniML, clone the project’s GitHub Repository and install the requirements.

git clone https://github.com/delvendahl/miniML.git

Hint

We recommend creating a virtual environment for miniML using Python version 3.9 or 3.10

The Python dependencies for miniML are:

• sklearn

• matplotlib

• h5py

• pandas

• numpy

• scipy

• tensorflow

• pyabf

To install all dependencies using pip, run the following command in your Python environment:

pip install -r requirements.txt

This will install everything you need to run miniML locally.

Important

The release of TensorFlow 2.16 and Keras 3 introduced breaking changes that raise an error when loading models trained with earlier TensorFlow versions. To avoid this, it is recommended to use TensorFlow 2.14 or 2.15.

miniML can be run on a GPU to speed model inference. Either CUDA or tensorflow-metal are required for GPU use. Installation instructions for these requirements may depend on the specific hardware and OS and can be found online.