Any examples of using a pre-trained vector from fasttext?

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I am starting a sentiment analysis project on a corpus of text. I would like to augment my work with a pre-trained fasttext vector (english wikipedia, https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md ).

I cannot seem to find any examples of using such a pre-trained vector with mxnet. Does anyone have some sample code they might be able to share? A link to a something that I wasn’t able to find for whatever reason?

Any general advice on doing word embeddings with mxnet would be great too…the documentation seems a bit thin overall in this area.

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I’d recommend keeping an eye on the Gluon NLP toolkit: http://gluon-nlp.mxnet.io/index.html

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I was just checking on this and indeed it seems that now GluonNLP has something which matches what I was originally after. :smiley: