Generating Embeddings with ELMo
Explore how to generate contextual word embeddings using the ELMo model, understanding its output layers and default vectors. Learn about other advanced embedding techniques including FastText’s subword approach, Swivel’s loss function improvements, and transformer-based embeddings, gaining insights to apply them in NLP tasks.
We'll cover the following...
We'll cover the following...
Once the input is prepared, generating embeddings is quite easy. First, we’ll transform the inputs to the stipulated format of the ELMo layer. Here, we are using some example titles from the BBC ...
# Titles of 001.txt - 005.txt in bbc/businesselmo_inputs = format_text_for_elmo(["Ad sales boost Time Warner profit","Dollar gains on Greenspan speech","Yukos unit buyer faces loan claim","High fuel prices hit BA's profits","Pernod takeover talk lifts Domecq"])
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