Simple translation demo showcasing our headliner package.

Related tags

Text Data & NLP python nlp demo neural-network tensorflow seq2seq neural-machine-translation
Overview

Headliner Demo

This is a demo showcasing our Headliner package. In particular, we trained a simple seq2seq model on an English-German dataset. We didn't train it very long so the model is not doing well as this was not our main goals anyway. For creating the app, we use Streamlit, a new open-source framework that lets users creating apps for machine learning projects very easily.

In fact, for the deployment, we only need six lines of code:

import streamlit as st
from headliner.model.summarizer_transformer import SummarizerTransformer

summarizer_transformer = SummarizerTransformer.load('model/transformer')

st.title('Type in some English')
title = st.text_input('How are you?')
st.write(summarizer_transformer.predict(title))

🚀 Quick Start

  1. Install all the packages: 
    pip install -r requirements.txt
  2. Run the demo: 
    streamlit run translation_demo.py
  3. View the Streamlit app in your browser: http://localhost:8501

© Copyright

See LICENSE for details.

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Comments
  • Deployments

    Deployments

    Hey this looks really fantastic, btw how did you deployed it on web. is it free or paid service and how you managed to run streamlit run __.py in deployment. please provide some helpful information.

    opened by imneonizer 0
Owner
Axel Springer News Media & Tech GmbH & Co. KG - Ideas Engineering
We are driving, shaping and coding the future of tech at Axel Springer.
Axel Springer News Media & Tech GmbH & Co. KG - Ideas Engineering
GitHub http://18.185.32.128:8501/
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