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🦷 O-NLP : orthodontic natural language processing

This repository contains the code used to conduct fine-tuning on OrthodonticQA (OQA).

Usage

To download the assets (dataset and pretrained model weights) required to reproduce the experiments use the following command.

python etc/build_cache.py assests.toml

We use TOML to configure the hyper-parameters for the run. The config/ directory contains the various configurations for the experiments from the paper.

scripts/ contains examples for usage with a SLURM cluster.

To launch a training run:

python main.py configs/pubmedbert_sft.toml

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language models for orthodontic literature

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