sz128/pretrained_word_embeddings
It is about how to load and aggregate pretrained word embeddings in pytorch, e.g., ELMo\BERT\XLNET.
When performing natural language processing tasks, this helps you retrieve meaningful numerical representations (word embeddings) for words in your text. It takes raw text and pre-trained language models like ELMo, BERT, or XLNet as input, and outputs aggregated word embeddings suitable for further analysis. This is for machine learning engineers and data scientists working on text-based applications.
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Use this if you need to transform text into high-quality word embeddings using popular pre-trained models and require flexible methods for combining token-level embeddings back into word-level representations.
Not ideal if you are not comfortable with Python and PyTorch, or if you primarily work with other deep learning frameworks.
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Python
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Last pushed
Mar 02, 2020
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/sz128/pretrained_word_embeddings"
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