Idea is to build a model which will take keywords as inputs and generate sentences as outputs.

Overview

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:

Comments
  • ERROR: Could not find a version that satisfies the requirement keytotext (from versions: none)

    ERROR: Could not find a version that satisfies the requirement keytotext (from versions: none)

    Hi,

    I tried to install keytotext via pip install keytotext --upgrade in local machine.

    but came across the following :

    ERROR: Could not find a version that satisfies the requirement keytotext (from versions: none)
    ERROR: No matching distribution found for keytotext
    

    My pip version is the latest. However, the above works just fine in colab. Please guide me through the fix?

    opened by abhijithneilabraham 6
  • Add finetuning model to keytotext

    Add finetuning model to keytotext

    Is your feature request related to a problem? Please describe. Its difficult to use it without fine-tuning on new corpus so we need to build script to finetune it on new corpus

    enhancement good first issue 
    opened by gagan3012 2
  • "Oh no." ?

    "Error running app. If this keeps happening, please file an issue."

    Ok,...sure? I know nothing about this app.

    Just saw your tweet, clicked the link to this repo, then clicked the link on the side. Got that message. Now what?

    Chrome browser, Linux.

    opened by drscotthawley 2
  • Add Citations

    Add Citations

    Is your feature request related to a problem? Please describe. Inspirations: https://towardsdatascience.com/data-to-text-generation-with-t5-building-a-simple-yet-advanced-nlg-model-b5cce5a6df45

    Describe the solution you'd like A clear and concise description of what you want to happen.

    Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

    Additional context Add any other context or screenshots about the feature request here.

    opened by gagan3012 1
  • Adding new models to keytotext

    Adding new models to keytotext

    Is your feature request related to a problem? Please describe. Adding new models to keytotext: https://huggingface.co/mrm8488/t5-base-finetuned-common_gen

    Describe the solution you'd like A clear and concise description of what you want to happen.

    Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

    Additional context Add any other context or screenshots about the feature request here.

    enhancement good first issue 
    opened by gagan3012 1
  • Inference API for Keytotext

    Inference API for Keytotext

    Is your feature request related to a problem? Please describe. It is difficult to host the UI on streamlit without API

    Describe the solution you'd like Inference API

    enhancement good first issue 
    opened by gagan3012 1
  • Create Better UI

    Create Better UI

    Is your feature request related to a problem? Please describe. The current UI is not functional It needs to be fixed

    Describe the solution you'd like Better UI with a nicer design

    enhancement 
    opened by gagan3012 1
  • Add `st.cache` to load model

    Add `st.cache` to load model

    Hi @gagan3012,

    Johannes from the Streamlit team here :) I am currently investigating why apps run over the resource limits of Streamlit Sharing and saw that your app was affected in the past few days.

    Thought I'd send you a small PR which should fix this. You've already been on a good way with using st.cache but it gets even better if you use it once more to load the model. This makes sure the model and tokenizer are only loaded once, which should make the app consume less memory (and not run into resource limits again! Plus, I've seen that it also works a bit faster now ;).

    Hope this works for you and let me know if you have any other questions! 🎈

    Cheers, Johannes

    opened by jrieke 1
  • ValueError: transformers.models.auto.__spec__ is None

    ValueError: transformers.models.auto.__spec__ is None

    'from keytotext import pipeline'

    While running the above line, it is showing this error . "ValueError: transformers.models.auto.spec is None"

    opened by varunakk 0
  • Update README.md

    Update README.md

    Description

    Motivation and Context

    How Has This Been Tested?

    Screenshots (if appropriate):

    Types of changes

    • [ ] Bug fix (non-breaking change which fixes an issue)
    • [ ] New feature (non-breaking change which adds functionality)
    • [ ] Breaking change (fix or feature that would cause existing functionality to change)

    Checklist:

    • [ ] My code follows the code style of this project.
    • [ ] My change requires a change to the documentation.
    • [ ] I have updated the documentation accordingly.
    • [ ] I have read the CONTRIBUTING document.
    opened by gagan3012 0
  • Update trainer.py

    Update trainer.py

    Description

    Motivation and Context

    How Has This Been Tested?

    Screenshots (if appropriate):

    Types of changes

    • [ ] Bug fix (non-breaking change which fixes an issue)
    • [ ] New feature (non-breaking change which adds functionality)
    • [ ] Breaking change (fix or feature that would cause existing functionality to change)

    Checklist:

    • [ ] My code follows the code style of this project.
    • [ ] My change requires a change to the documentation.
    • [ ] I have updated the documentation accordingly.
    • [ ] I have read the CONTRIBUTING document.
    opened by gagan3012 0
  • Pipeline error on fresh install

    Pipeline error on fresh install

    Hi I'm getting this on a first run and fresh install

    Global seed set to 42 Traceback (most recent call last): File "C:\Users\skint\PycharmProjects\spacynd2\testdata.py", line 1, in <module> from keytotext import pipeline File "C:\Users\skint\venv\lib\site-packages\keytotext\__init__.py", line 11, in <module> from .dataset import make_dataset File "C:\Users\skint\venv\lib\site-packages\keytotext\dataset.py", line 1, in <module> from cv2 import randShuffle ModuleNotFoundError: No module named 'cv2'

    opened by skintflickz 0
  • New TypeError: __init__() got an unexpected keyword argument 'progress_bar_refresh_rate'

    New TypeError: __init__() got an unexpected keyword argument 'progress_bar_refresh_rate'

    I have imported the model and necessary libraries. I am getting the below error in google colab. I have used this model earlier also few months back and it was working fine. This is the new issue I am facing recently with the same code.


    TypeError: init() got an unexpected keyword argument 'progress_bar_refresh_rate'

    Imported libraries:

    !pip install keytotext --upgrade !sudo apt-get install git-lfs

    from keytotext import trainer

    Training Model:

    model = trainer() model.from_pretrained(model_name="t5-small") model.train(train_df=df_train_final, test_df=df_test, batch_size=3, max_epochs=5,use_gpu=True) model.save_model()

    Have attached error screenshot

    • OS: Windows
    • Browser Chrome Error
    opened by aishwaryapisal9 2
  • Update trainer.py

    Update trainer.py

    Delete progress_bar_refresh_rate in trainer.py

    Description

    delete progress_bar_refresh_rate=5, since this keyword argument is no longer supported by the latest version (1.7.0) of PyTorch.Lightning.Trainer module

    Motivation and Context

    having this argument fails the training process

    How Has This Been Tested?

    Ran key to text on the custom dataset before and after August 2nd, 2022. Changes in the new version of Pytorch Lightning's Trainer were put into effect on that date where the above argument was removed and hence, the custom training failed since that day.

    Screenshots (if appropriate):

    Types of changes

    • [x] Bug fix (non-breaking change which fixes an issue)
    • [ ] New feature (non-breaking change which adds functionality)
    • [ ] Breaking change (fix or feature that would cause existing functionality to change)

    Checklist:

    • [x] My code follows the code style of this project.
    • [x] My change requires a change to the documentation.
    • [ ] I have updated the documentation accordingly.
    • [ ] I have read the CONTRIBUTING document.
    opened by anath2110benten 0
  • Why is cv2 required?

    Why is cv2 required?

    https://github.com/gagan3012/keytotext/blob/6f807b940f5e2fdeb755ed085b40af7c0fa5e87e/keytotext/dataset.py#L1

    I'm using this framework to generate text from knowlege graph. Python interpreter keeps throwing "cv2 not installed" exception. Looks like the pip package doesn't contains cv2 as dependancy. I tried to delete this line in source code, the model works well. Is this line necessary for this project? Concerning about adding opencv to pip package? Thanks for your concern.

    opened by ChunxuYang 0
  • Hi, I notice that given the same input keywords, across different runs, the generated text are the same, even setting different seeds by 'pl.seed_everything(..)'.

    Hi, I notice that given the same input keywords, across different runs, the generated text are the same, even setting different seeds by 'pl.seed_everything(..)'.

    Is your feature request related to a problem? Please describe. A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]

    Describe the solution you'd like A clear and concise description of what you want to happen.

    Describe alternatives you've considered A clear and concise description of any alternative solutions or features you've considered.

    Additional context Add any other context or screenshots about the feature request here.

    opened by RuiFeiHe 6
Releases(v1.5.0)
Owner
Gagan Bhatia
Software Developer | Machine Learning Enthusiast
Gagan Bhatia
To be a next-generation DL-based phenotype prediction from genome mutations.

Sequence -----------+-- 3D_structure -- 3D_module --+ +-- ? | |

Eric Alcaide 18 Jan 11, 2022
Big Bird: Transformers for Longer Sequences

BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the c

Google Research 457 Dec 23, 2022
Uses Google's gTTS module to easily create robo text readin' on command.

Tool to convert text to speech, creating files for later use. TTRS uses Google's gTTS module to easily create robo text readin' on command.

0 Jun 20, 2021
This repo stores the codes for topic modeling on palliative care journals.

This repo stores the codes for topic modeling on palliative care journals. Data Preparation You first need to download the journal papers. bash 1_down

3 Dec 20, 2022
This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.

UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s

Google 1.4k Dec 28, 2022
中文无监督SimCSE Pytorch实现

A PyTorch implementation of unsupervised SimCSE SimCSE: Simple Contrastive Learning of Sentence Embeddings 1. 用法 无监督训练 python train_unsup.py ./data/ne

99 Dec 23, 2022
Active learning for text classification in Python

Active Learning allows you to efficiently label training data in a small-data scenario.

Webis 375 Dec 28, 2022
Natural Language Processing Tasks and Examples.

Natural Language Processing Tasks and Examples With the advancement of A.I. technology in recent years, natural language processing technology has bee

Soohwan Kim 53 Dec 20, 2022
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab

HUSEIN ZOLKEPLI 1.7k Dec 30, 2022
MicBot - MicBot uses Google Translate to speak everyone's chat messages

MicBot MicBot uses Google Translate to speak everyone's chat messages. It can al

2 Mar 09, 2022
Tutorial to pretrain & fine-tune a 🤗 Flax T5 model on a TPUv3-8 with GCP

Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava

Gabriele Sarti 41 Nov 18, 2022
Train BPE with fastBPE, and load to Huggingface Tokenizer.

BPEer Train BPE with fastBPE, and load to Huggingface Tokenizer. Description The BPETrainer of Huggingface consumes a lot of memory when I am training

Lizhuo 1 Dec 23, 2021
Python api wrapper for JellyFish Lights

Python api wrapper for JellyFish Lights The hope is to make this a pip installable package Current capabalilities: Connects to a local JellyFish Light

10 Dec 18, 2022
InferSent sentence embeddings

InferSent InferSent is a sentence embeddings method that provides semantic representations for English sentences. It is trained on natural language in

Facebook Research 2.2k Dec 27, 2022
A Telegram bot to add notes to Flomo.

flomo bot 使用 Telegram 机器人发送笔记到你的 Flomo. 你需要有一台可访问 Telegram 的服务器。 Steps @BotFather 新建机器人,获取 token Flomo 官网获取 API,链接 https://flomoapp.com/mine?source=in

Zhen 44 Dec 30, 2022
Voice Assistant inspired by Google Assistant, Cortana, Alexa, Siri, ...

author: @shival_gupta VoiceAI This program is an example of a simple virtual assitant It will listen to you and do accordingly It will begin with wish

Shival Gupta 1 Jan 06, 2022
BiNE: Bipartite Network Embedding

BiNE: Bipartite Network Embedding This repository contains the demo code of the paper: BiNE: Bipartite Network Embedding. Ming Gao, Leihui Chen, Xiang

leihuichen 214 Nov 24, 2022
Guide to using pre-trained large language models of source code

Large Models of Source Code I occasionally train and publicly release large neural language models on programs, including PolyCoder. Here, I describe

Vincent Hellendoorn 947 Dec 28, 2022
ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体

ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体,包括上市公司所属行业关系、行业上级关系、产品上游原材料关系、产品下游产品关系、公司主营产品、产品小类共6大类。 上市公司4,654家,行业511个,产品95,559条、上游材料56,824条,上级行业480条,下游产品390条,产品小类52,937条,所属行业3,946条。

liuhuanyong 415 Jan 06, 2023
Addon for adding subtitle files to blender VSE as Text sequences. Using pysub2 python module.

Import Subtitles for Blender VSE Addon for adding subtitle files to blender VSE as Text sequences. Using pysub2 python module. Supported formats by py

4 Feb 27, 2022