A simple example for how to build your own model using AllenNLP as a dependency. An explanation of all of the code in this repository is given in the part 1 and part 2 of the AllenNLP tutorial.

There are two main pieces of code you need to write in order to make a new model: a DatasetReader and a Model. In this repository, we constructed a DatasetReader for reading academic papers formatted as a JSON lines file (you can see an example of the data in tests/fixtures/s2_papers.jsonl). We then constructed a model to classify the papers given some label (which we specified as the paper's venue in the DatasetReader). Finally, we added a script to use AllenNLP's training commands from a third-party repository, and an experiment configuration for running a real model on real data.

To train this model, after setting up your development environment by running pip install -r requirements.txt, you run:

allennlp train experiments/venue_classifier.json -s /tmp/your_output_dir_here --include-package my_library

This example was written by the AllenNLP team. You can see a similar example repository written by others here.