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View Code? Open in Web Editor NEWPytorch implementation of "Graph Convolutional Networks for Text Classification"
Pytorch implementation of "Graph Convolutional Networks for Text Classification"
I have a dataset which consists of 39k unique words, that means i should create a graph for 39k nodes and also the edges connecting the nodes to their particular document using tf-idf scores as weight, please help me on how the approach should be for creating the graph as i am running out of memory every time.
RAM : 16GB
how can we apply this on other datasets and select labels ?
Hi,
how can I save the new updated embeddings for future use?
Thank you
I am trying to run the code on my dataset. Its a public dataset having text and the respective class name. The text for each class name is about one line.
Do I need to change the code because I don't have the header like you have in yours?
args.pkl is not available in the data folder. could you please upload that for the users? Thanks!
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