Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
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This is a PyTorch tutorial for the ACL'16 paper End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

This repository includes

  • IPython Notebook of the tutorial
  • Data folder
  • Setup Instructions file
  • Pretrained models directory (The notebook will automatically download pre-trained models into this directory, as required)


Anirudh Ganesh

Peddamail Jayavardhan Reddy


The best way to install pytorch is via the pytorch webpage


Creating new Conda environment

conda create -n pytorch python=3.5

Activate the condo environment

source activate pytorch

Setting up notebooks with specific python version (python 3.5)

conda install notebook ipykernel
ipython kernel install --user

PyTorch Installation command:

conda install pytorch torchvision -c pytorch

NumPy installation

conda install -c anaconda numpy

Download GloVe vectors and extract glove.6B.100d.txt into "./data/" folder

wget http://nlp.stanford.edu/data/glove.6B.zip

Data Files

You can download the data files from within this repo over here