Skip to main content

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 CodeFactor

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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

keytotext-2.0.0.tar.gz (744.9 kB view details)

Uploaded Source

Built Distribution

keytotext-2.0.0-py3-none-any.whl (11.2 kB view details)

Uploaded Python 3

File details

Details for the file keytotext-2.0.0.tar.gz.

File metadata

  • Download URL: keytotext-2.0.0.tar.gz
  • Upload date:
  • Size: 744.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.27.1

File hashes

Hashes for keytotext-2.0.0.tar.gz
Algorithm Hash digest
SHA256 d61865fd4c8ff3700ef2da14827d65b95ac1717c9293fa03290a72307e739167
MD5 3e0cd87e52f0cbcc397775897b6076ff
BLAKE2b-256 1c40a377f02d76ad045b79e15c1dd60efaf192fbb562ebe300e468d681ec81d9

See more details on using hashes here.

File details

Details for the file keytotext-2.0.0-py3-none-any.whl.

File metadata

  • Download URL: keytotext-2.0.0-py3-none-any.whl
  • Upload date:
  • Size: 11.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.27.1

File hashes

Hashes for keytotext-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b7581db3c8aa689f5b5462beb0cd6535c400c61f3b0ae79d8bdbd1070e9db778
MD5 5239590b09e0eeaa1521be038d5c1f30
BLAKE2b-256 7500b285e1def231868d953195fb0fd09da7d6bfafe5b16a234de71ac3331d17

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page