# BERT Inference Using PopTorch ## 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/mrm8488/bert-medium-finetuned-squadv2) 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 default `context.txt` contains the context sequence - `--questions-file`, by default `questions.txt`, contains the sequences of "questions" that are used as inputs by the model and then completed as "answers" as outputs to the model. ## Requirements - A Poplar SDK environment enabled, with PopTorch installed (see the [Getting Started](https://docs.graphcore.ai/en/latest/getting-started.html) guide for your IPU system) - Python packages installed with `python -m pip install -r requirements.txt` ## Execution The example can be run from the command line: ```:bash python3 bert_inference.py ```