## Overview
This example shows how to use PopTorch to run inference on a pre-trained BERT model. The pre-trained model is downloaded from Hugging Face (https://huggingface.co/transformers/model_doc/bert.html) and compiled to run on the IPU. The model has been already been fine tuned on the SQuADv2 corpus and is configured for a question-answering task.
Two text files are used to provide inputs to the network:
--context-file, by defaultcontext.txtcontains the context sequence--questions-file, by defaultquestions.txt, contains the sequences of "questions" that are used as inputs by the model and then completed as "answers" as outputs to the model.
Install the Python dependencies by running:
python3 -m pip install -r requirements
Ensure the Poplar SDK 1.2.x is installed and configured to run in the current environment.
The example can be run from the command line:
python3 bert_inference.py