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Understanding Hugging Face's implementation of BERT and GPT2

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play-with-transformers

Played around with Hugging Face's implementation of BERT and GPT2 for my understanding. The notebook includes:

  1. Bert as an encoder, GPT2 as a decoder.
  2. Simple examples of how vectors representations look like including the length of each vector.
  3. How similar representations correspond to spatial proximity.

Open BERT_GPT2_Play.ipynb in colab from the link and create your own copy. Further comments inline.

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