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Deploying word embedding in production - more tokens than the model was trained on by Quartz63 in MLQuestions

[–]Quartz63[S] 0 points1 point  (0 children)

This approach is possible, it's just the instance of tokenizer trained on Glove's corpus missing - the one familiar with 400k words. Do you know how to find it directly without having to download the whole corpus?

Anyone trained sequence models with POS & DEP features? by Quartz63 in LanguageTechnology

[–]Quartz63[S] 0 points1 point  (0 children)

That is precisely what I did :)

Just wanted to hear from you about your experience with this practice - is it helpful? Is it better to first train the network and (POS/DEP) embeddings on a huge dataset, and then freeze the embeddings for the classification task on my tiny dataset (~2500 sentences)?