Removing a couple of other old unnecessary comments
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# Step 1: Slurp the dataset up, tokenize each sentence, and store as docs -> sentences -> tokens
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# Step 2: Walk over the dataset, using the Google BERT logic to concatenate sentences into training examples
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# Step 3: Write out the examples, possibly as Torch tensors?
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from argparse import ArgumentParser
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from argparse import ArgumentParser
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from pathlib import Path
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from pathlib import Path
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from tqdm import tqdm, trange
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from tqdm import tqdm, trange
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