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zhongkaifu avatar zhongkaifu commented on May 18, 2024 2

Thanks @GeorgeS2019 for your suggestion.

I know sub-word tokenization is really useful for text generation tasks, such as MT task could get 2~3pt BLEU scores gain on average and some NN frameworks did integrate sub-word tokenization, such as Marian uses built-in SentencePiece for data processing,

However, since it's a part of data processing, and include several key steps, such as model training, encoding and decoding, I prefer to create separate project for it rather than integrating it to Seq2SeqSharp project.

So, in my opinion, my plan would be 1) Create a project for BPE training/encoding/decoding called SubwordSharp. :) 2) Create a training pipeline to integrate SubwordSharp BPE model training, BPE encoding, and Seq2SeqSharp training, BPE decoding and evaluation steps together, and 3) Create a runtime pipeline to integrate BPE encoding, Seq2SeqSharp inference, BPE decoding together.

from seq2seqsharp.

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