Text Generation Using Keywords
Project description
keytotext
Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
Potential use case can include:
- Marketing
- Search Engine Optimization
- Topic generation etc.
- Fine tuning of topic modeling models
Model:
Keytotext is based on the Amazing T5 Model:
k2t
: Modelk2t-tiny
: Modelk2t-base
: Modelmrm8488/t5-base-finetuned-common_gen
(by Manuel Romero): Model
Training Notebooks can be found in the Training Notebooks
Folder
Note: To add your own model to keytotext Please read Models Documentation
Usage:
Example Notebooks can be found in the Notebooks
Folder
pip install keytotext
UI:
pip install streamlit-tags
This uses a custom streamlit component built by me: GitHub
API:
The API is hosted in the Docker container and it can be run quickly. Follow instructions below to get started
docker pull gagan30/keytotext
docker run -dp 8000:8000 gagan30/keytotext
This will start the api at port 8000 visit the url below to get the results as below:
http://localhost:8000/api?data=["India","Capital","New Delhi"]
Note: The Hosted API is only available on demand
BibTex:
To quote keytotext please use this citation
@misc{bhatia,
title={keytotext},
url={https://github.com/gagan3012/keytotext},
journal={GitHub},
author={Bhatia, Gagan}
}
References:
- https://towardsdatascience.com/data-to-text-generation-with-t5-building-a-simple-yet-advanced-nlg-model-b5cce5a6df45 (Mathew Alexander)
- https://github.com/patil-suraj/question_generation (Suraj Patil)
- Amazing Video by 1LittleCoder here: https://www.youtube.com/watch?v=I0iBzP-SxFY about keytotext
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