Setup CI
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version: 2
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jobs:
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build:
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working_directory: ~/pytorch-pretrained-BERT
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docker:
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- image: circleci/python:3.7
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steps:
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- checkout
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- run: sudo pip install --progress-bar off .
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- run: sudo pip install pytest
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- run: python -m pytest -sv tests/
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# PyTorch Pretrained Bert
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[](https://circleci.com/gh/huggingface/pytorch-pretrained-BERT)
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This repository contains an op-for-op PyTorch reimplementation of [Google's TensorFlow repository for the BERT model](https://github.com/google-research/bert) that was released together with the paper [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) by Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova.
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This implementation is provided with [Google's pre-trained models](https://github.com/google-research/bert), examples, notebooks and a command-line interface to load any pre-trained TensorFlow checkpoint for BERT is also provided.
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