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1
Intro
2
BERT Base Network
3
Sentence Vectors and Similarity
4
The Data and Model
5
Two Approaches
6
Tokenizing Sentences
7
Creating last_hidden_state Tensor
8
Creating Sentence Vectors
9
Cosine Similarity
Description:
Learn how to implement sentence similarity using BERT and PyTorch in this 21-minute Python tutorial. Explore the power of highly-dimensional NLP techniques as you convert sentences into vectors and measure their semantic similarity. Follow along step-by-step to tokenize sentences, create hidden state tensors, generate sentence vectors, and calculate cosine similarity. Gain practical insights into BERT's architecture and its application in natural language processing tasks.

Sentence Similarity With Transformers and PyTorch

James Briggs
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