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skills-taxonomy-v2

Setup

  • Meet the data science cookiecutter requirements, in brief:
    • Install: git-crypt
    • Have a Nesta AWS account configured with awscli
  • Run make install to configure the development environment:
    • Setup the conda environment
    • Configure pre-commit
    • Configure metaflow to use AWS

Running locally

When you are running scripts from this repo for the first time you need to create the environment by running make conda-create to create the conda environment. Then everytime after this you can activate it using conda activate skills-taxonomy-v2. If you update the requirements then run make conda-update.

As a one off, if needed, you will also have to run:

conda install pytorch torchvision torchaudio -c pytorch

to use pytorch, and

conda install -c conda-forge spacy==3.0.0
python -m spacy download en_core_web_sm

for spaCy.

Then

conda install cdlib=0.2.3

(this doesn't work when added to the environment.yaml).

to install xgboost:

conda install -c anaconda py-xgboost

or

conda install -c conda-forge py-xgboost

if you aren't using anaconda.

Running on EC2

Check out this if you need to set up a new instance. To connect to the one for this project there is one called i-0a193c947acc1e53c, you need to download the relevant nesta_core.pem file from s3://nesta-production-config/nesta_core.pem.

Connect to it with:

chmod 400 nesta_core.pem
ssh -i "nesta_core.pem" [email protected]

(you may need to link to correct nesta_core.pem location).

EC2 will have the cuda GPU neccessary to get the spacy transformers word embeddings. To get this to work on an EC2 instance:

pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
pip install -U spacy[cuda102,transformers]
pip install transformers[sentencepiece]
python -m spacy download en_core_web_trf

Note this won't work on a macbook since they don't have a NVIDIA CUDA GPU.

Stop:

aws ec2 stop-instances --instance-ids i-0a193c947acc1e53c

Contributor guidelines

Technical and working style guidelines

Project based on Nesta's data science project template (Read the docs here).