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https://github.com/gagan3012/keytotext

Keywords to Sentences
https://github.com/gagan3012/keytotext

api docker huggingface-transformers keytotext keywords nlp sentences streamlit t5

Last synced: 1 day ago
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Keywords to Sentences

Host: GitHub
URL: https://github.com/gagan3012/keytotext
Owner: gagan3012
License: mit
Created: 2021-02-20T13:08:44.000Z (almost 4 years ago)
Default Branch: master
Last Pushed: 2023-08-15T22:12:17.000Z (over 1 year ago)
Last Synced: 2025-02-10T11:04:57.275Z (8 days ago)
Topics: api, docker, huggingface-transformers, keytotext, keywords, nlp, sentences, streamlit, t5
Language: Jupyter Notebook
Homepage: https://share.streamlit.io/gagan3012/keytotext/UI/app.py
Size: 4.04 MB
Stars: 450
Watchers: 13
Forks: 57
Open Issues: 19
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Citation: CITATION.cff

Awesome Lists containing this project

README

        
keytotext


[![pypi Version](https://img.shields.io/pypi/v/keytotext.svg?logo=pypi&logoColor=white)](https://pypi.org/project/keytotext/)

[![Downloads](https://static.pepy.tech/personalized-badge/keytotext?period=total&units=none&left_color=grey&right_color=orange&left_text=Pip%20Downloads)](https://pepy.tech/project/keytotext)

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gagan3012/keytotext/blob/master/notebooks/K2T.ipynb)

[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/UI/app.py)

[![API Call](https://img.shields.io/badge/-FastAPI-red?logo=fastapi&labelColor=white)](https://github.com/gagan3012/keytotext#api)

[![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://hub.docker.com/r/gagan30/keytotext)

[![HuggingFace](https://img.shields.io/badge/%F0%9F%A4%97-Models%20on%20Hub-yellow)](https://huggingface.co/models?filter=keytotext)

[![Documentation Status](https://readthedocs.org/projects/keytotext/badge/?version=latest)](https://keytotext.readthedocs.io/en/latest/?badge=latest)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![CodeFactor](https://www.codefactor.io/repository/github/gagan3012/keytotext/badge)](https://www.codefactor.io/repository/github/gagan3012/keytotext)

![keytotext](https://socialify.git.ci/gagan3012/keytotext/image?description=1&forks=1&language=1&owner=1&stargazers=1&theme=Light)

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](https://img.shields.io/badge/%F0%9F%A4%97-Models%20on%20Hub-yellow)](https://huggingface.co/models?filter=keytotext)

- `k2t`: [Model](https://huggingface.co/gagan3012/k2t)

- `k2t-base`: [Model](https://huggingface.co/gagan3012/k2t-base)

- `mrm8488/t5-base-finetuned-common_gen` (by Manuel Romero): [Model](https://huggingface.co/mrm8488/t5-base-finetuned-common_gen)

Training Notebooks can be found in the [`Training Notebooks`](https://github.com/gagan3012/keytotext/tree/master/notebooks) Folder

**Note**: To add your own model to keytotext Please read [`Models Documentation`](https://github.com/gagan3012/keytotext/blob/master/docs/MODELS.md)

## Usage:

Example usage: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gagan3012/keytotext/blob/master/notebooks/K2T.ipynb)

Example Notebooks can be found in the [`Notebooks`](https://github.com/gagan3012/keytotext/tree/master/examples) Folder

```shell script

pip install keytotext

```

![carbon (3)](https://user-images.githubusercontent.com/49101362/116220679-90e64180-a755-11eb-9246-82d93d924a6c.png)

## 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`](https://github.com/gagan3012/keytotext/blob/master/docs/TRAINER.md)

Trainer example here: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gagan3012/keytotext/blob/master/notebooks/Trainer.ipynb)

```python

from keytotext import trainer

```

![carbon (6)](https://user-images.githubusercontent.com/49101362/125130656-5989fe80-e0cf-11eb-8c07-c659767911b4.png)

## UI:

UI: [![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/UI/app.py)

```shell script

pip install streamlit-tags

```

This uses a custom streamlit component built by me: [GitHub](https://github.com/gagan3012/streamlit-tags)

![image](https://user-images.githubusercontent.com/49101362/116162205-fc042980-a6fd-11eb-892e-8f6902f193f4.png)

## API:

API: [![API Call](https://img.shields.io/badge/-Open%20with%20FastAPI-red?logo=fastapi&labelColor=white)](http://localhost:8000/api?data=[%22India%22,%22Capital%22,%22New%20Delhi%22])

[![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://hub.docker.com/r/gagan30/keytotext)

The API is hosted in the Docker container and it can be run quickly.

Follow instructions below to get started

```shell script

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](https://user-images.githubusercontent.com/49101362/117046515-c56e7600-acde-11eb-8a20-7e1ab5f0de02.png)

Note: The Hosted API is only available on demand

## BibTex:

To quote keytotext please use this citation

```bibtex

@misc{bhatia, 

      title={keytotext},

      url={https://github.com/gagan3012/keytotext}, 

      journal={GitHub}, 

      author={Bhatia, Gagan}

}

```

# References 

- https://github.com/Shivanandroy/simpleT5 (Shivanand Roy)

- https://github.com/patil-suraj/question_generation (Suraj Patil)

- https://github.com/MathewAlexander/T5_nlg (Mathew Alexander)

## Articles about keytotext:

- https://towardsdatascience.com/data-to-text-generation-with-t5-building-a-simple-yet-advanced-nlg-model-b5cce5a6df45 (Mathew Alexander)

- Amazing Video by [1LittleCoder](https://twitter.com/1littlecoder) here: https://www.youtube.com/watch?v=I0iBzP-SxFY about keytotext

- https://medium.com/mlearning-ai/generating-sentences-from-keywords-using-transformers-in-nlp-e89f4de5cf6b (Prakhar Mishra)