Text Generator

Text Generator is an End-to-End NLP model which can generate text based on given input deployed on Streamlit

Model : GPT-2

Library : 🤗 Hugging Face

Pre-Trained on : English language using a causal language modeling (CLM)

View Deployed Demo on Streamlit

• Just open above link and select Text Generator

Demo

Run Locally

• Clone the project

  git clone https://github.com/srajanseth84/Text-Generator-using-GPT2.git

• Go to the project directory

  cd Text-Generator-using-GPT2

• Create venv

  python3 -m virtualenv venv 

• Activate the venv

  source venv/bin/activate

• Install dependencies

  pip install -r requirements.txt

• Start the server

  streamlit run app.py 

GPT-2 MODEL DESCRIPTION

• GPT-2 is a transformers model pretrained on a very large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was trained to guess the next word in sentences.

• More precisely, inputs are sequences of continuous text of a certain length and the targets are the same sequence, shifted one token (word or piece of word) to the right. The model uses internally a mask-mechanism to make sure the predictions for the token i only uses the inputs from 1 to i but not the future tokens.

• This way, the model learns an inner representation of the English language that can then be used to extract features useful for downstream tasks. The model is best at what it was pretrained for however, which is generating texts from a prompt.

Dependencies

• Tensorflow
• Hugging Face 🤗
• Streamlit
• GPT-2

Tech Stack

• Front-End: Streamlit
• Cloud: Streamlit Cloud
• DL-Framework: Hugging Face

Reference

• Hugging Face 🤗
• GPT-2

Authors

• @srajanseth84