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next_word_prediction's Introduction

Next word prediction

Simple application using transformers models to predict next word or a masked word in a sentence.

The purpose is to demo and compare the main models available up to date.

The first load take a long time since the application will download all the models. Beside 6 models running, inference time is acceptable even in CPU.

Application

This app implements two variants of the same task (predict token). The first one consider the is at end of the sentence, simulating a prediction of the next word of the sentece.

The second variant is necessary to include a token where you want the model to predict the word.

Word prediction

Running

cd web-app
python app.py

Open your browser http://localhost:8000

next_word_prediction's People

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next_word_prediction's Issues

Google Colab Version. Flask issue ๐Ÿ“

Very grateful for the interface. Thank you.
I'm trying to make this interface more accessible to others by providing a Colab version of it. Unfortunately, I'm having a bit of an issue with getting the flask server to be integrated in Colab. This is as far as I've gotten. Maybe you can take it from there?

Colab of Next Word Prediction

Current issue is that "ngrok" is causing the error:
TypeError: new_run() got an unexpected keyword argument 'host'
I'm not familiar enough with flask or ngrok to solve it, but it would be super helpful if you can have a look.

Model name 'bart-large' was not found

When I tried to run the application I got the following error:

Traceback (most recent call last):
  File "app.py", line 4, in <module>
    import main
  File "/home/moussa/Documents/next_word_prediction/main.py", line 18, in <module>
    bart_tokenizer = BartTokenizer.from_pretrained('bart-large')
  File "/home/moussa/anaconda3/lib/python3.7/site-packages/transformers/tokenization_utils.py", line 911, in from_pretrained
    return cls._from_pretrained(*inputs, **kwargs)
  File "/home/moussa/anaconda3/lib/python3.7/site-packages/transformers/tokenization_utils.py", line 1014, in _from_pretrained
    list(cls.vocab_files_names.values()),
OSError: Model name 'bart-large' was not found in tokenizers model name list (facebook/bart-large, facebook/bart-large-mnli, facebook/bart-large-cnn, facebook/bart-large-xsum). We assumed 'bart-large' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.json', 'merges.txt'] but couldn't find such vocabulary files at this path or url.

How do I do it on a corpus of search engine queries

Hi renatoviolin,is it possible to perform similar recommendations of words for search queries if I have already have a large corpus of search queries.I expect it needs a how training may I how do I do it on these tokenizers?

Thanks in advance!!

Request

Can you make a web demo accessible to everyone?

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