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- 1. Make sure you have `python3.6` and the `pip` module installed. We recommend using [conda environments](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html). 1. Navigate to the root folder of this repository (the same folder that contains this README file) and run `pip install -r requirements.txt`. Note: If you are using a conda env and any packages fail to compile during this step, you may need to first install those packages separately with `conda install package_name`. 1. Wait for all the requirements to be downloaded and installed. 1. Run `python setup.py install` to install this module. This will also download the Word2vec model files. If the download fails, manually download the [model](https://storage.googleapis.com/mat2vec/pretrained_embeddings), [word embeddings](https://storage.googleapis.com/mat2vec/pretrained_embeddings.wv.vectors.npy) and [output embeddings](https://storage.googleapis.com/mat2vec/pretrained_embeddings.trainables.syn1neg.npy) and put them in mat2vec/training/models. 1. Finalize your chemdataextractor installation by executing ``cde data download`` (You may need to restart your virtual environment for the cde command line interface to be found). 1. You are ready to go!