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Text Generation Using Keywords

Project description

keytotext

pypi Version Downloads Open In Colab Streamlit App API Call Docker Call HuggingFace Documentation Status Code style: black

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: HuggingFace

  • k2t: Model
  • k2t-base: Model
  • mrm8488/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 usage: Open In Colab

Example Notebooks can be found in the Notebooks Folder

pip install keytotext

carbon (3)

Trainer:

Keytotext now has a trainer class than be used to train and finetune any T5 based model on new data. Updated Trainer docs here: Docs

Trainer example here: Open In Colab

from keytotext import trainer

carbon (6)

UI:

UI: Streamlit App

pip install streamlit-tags

This uses a custom streamlit component built by me: GitHub

image

API:

API: API Call Docker Call

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"]

k2t_json

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

Articles about keytotext:

Project details


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