Are we able to use this for building a chatbot for another language?
Sure, the tools are language agnostic. Unfortunately all of our current data sets are in English. We would greatly welcome dialogue datasets in other languages.
Thank you for answering my question. For training for other language, is it fine to only change the dataset in other language? What else do we need?
It鈥檚 hard to say, the situation you鈥檝e described is too vague. Ostensibly yes, but maybe not depending on your situation.
The main issue you will face is the tokenization. Otherwise, everything should work. Languages like Spanish work almost entirely out of the box whereas Chinese will take some work.
We just added c3, which is a Chinese reading comprehension dataset. It's not dialogue, but it's a start! #2665.
@stephenroller @jsedoc
Thank you for your suggestions.
For the tokenization case, where can I change it?
Suppose I have a tokenization model for my own language, where can I update the code to work?
If you want to use a BPE tokenizer, you can follow HuggingFace's instructions to train your own. If you have a premade tokenizer, you can add say wickky_tokenize to this class:
def wickky_tokenize(self, text):
return text.split("x")
And then use rest of parlai with the --dict-tokenizer wickky argument.
@stephenroller Thank you so much! It works!
@stephenroller I have one more question sir. When we predict say in interactive mode, does it use the tokenizer we passed while training for the user input message ?
Yes.
Hello @stephenroller
I have one question. How can I use sentence piece tokenizer?
Most helpful comment
The main issue you will face is the tokenization. Otherwise, everything should work. Languages like Spanish work almost entirely out of the box whereas Chinese will take some work.