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This repository has been archived by the owner on Aug 20, 2024. It is now read-only.
I was trying to play with this to see the performance of a DMN but I found it pretty hard to write even a short "story" without using an out-of-vocabulary word. Some of the words you can't use are very common like: "has", "it's", "an".
It is possible to let the prediction still run even if out-of-vocabulary words exist? I'd imagine it would degrade performance, but it would make the demo much easier to use.
The text was updated successfully, but these errors were encountered:
using out of vocabulary words is not there as it is out of the scope of Facebook's bAbI dataset is trying to solve. i think it is possible to add support in the backend, but it might lead to unexpected results. The models were trained on very limited vocabulary.
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I was trying to play with this to see the performance of a DMN but I found it pretty hard to write even a short "story" without using an out-of-vocabulary word. Some of the words you can't use are very common like: "has", "it's", "an".
It is possible to let the prediction still run even if out-of-vocabulary words exist? I'd imagine it would degrade performance, but it would make the demo much easier to use.
The text was updated successfully, but these errors were encountered: