Skip to content

Latest commit

 

History

History
22 lines (13 loc) · 978 Bytes

File metadata and controls

22 lines (13 loc) · 978 Bytes

Reddit Rep 2

New ideas for measuring reputation based on graph neaural nets.

An example of how to use the tools here is present in main.py.

Reddit data is avaliable at https://files.pushshift.io/reddit/comments/

Setting up GloVe vectors

The setup for GloVe embeddings follows from this tutorial: https://medium.com/@martinpella/how-to-use-pre-trained-word-embeddings-in-pytorch-71ca59249f76

  1. Download the word vectors glove.6B.zip from: https://nlp.stanford.edu/projects/glove/
  2. Extract the zip folder contents into machine_learning/glove
  3. run cd machine_learning && python create_glove_embedding.py. This will process the word vectors and save the results into pkl files.

Trained a Model

  1. if not done already, run pip install -r requirements.txt
  2. run python process_trees.py. This creates a pickle file of 100 processed trees
  3. cd to machine_learning and run python glove_gat.py. This trains the model on the pickle file just created