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Description
Hi, I am trying to replicate your Text Classification results so that I can then use your models on my own data set, but I am unable to get any of the text models working at all.
The problem I am running into is that GloVe is outputting a tensor of floats but the embedding layer TextCCT starts with seems to be expecting a tensor of integers. Is there some configuration option I am missing?
This is a follow-up to #73, which I don't have permissions to re-open.
Also in that issue, @stevenwalton mentioned
The insights from our vision work may not be as useful for NLP tasks, where many of these problems don't exist (transformers are quite successful on small datasets without pre-training).
Could you point me to any specific models? I liked your models because they were transformers with low parameter count and showed good performance on small data sets without pre-training. Any other transformers I can find that perform well on a small data sets have huge parameter counts and must have been pre-trained on some huge data set beforehand, which I am trying to avoid if possible (though I am going to try both to compare anyway).
Thanks for your help!