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...Besides adding or removing elements from the set, we need fast functions to compute the intersection, the union, the difference between sets, and so on. To implement a set of integers, a particularly appealing strategy is the bitmap (also called bitset or bit vector).
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any pre trained transformer model if you install spacy-transformers. ...