Almost State-of-the-art Text Generation library

Overview

Ps: we are adding transformer model soon

Text Gen 🐐

Downloads python tensorflow PyPI

Almost State-of-the-art Text Generation library

Text gen is a python library that allow you build a custom text generation model with ease 😄 Something sweet built with Tensorflow and Pytorch(coming soon) - This is the brain of Rosalove ai (https://rosalove.xyz/)

How to use it

Install text-gen

pip install -U text-gen

import the library

from text_gen import ten_textgen as ttg

Load your data. your data must be in a text format.

Download the example data from the example folder

load data

data = 'rl.csv'
text = ttg.loaddata(data)

build our Model Architeture

pipeline = ttg.tentext(text)
seq_text = pipeline.sequence(padding_method = 'pre')
configg = pipeline.configmodel(seq_text, lstmlayer = 128, activation = 'softmax', dropout = 0.25)

train model

model_history = pipeline.fit(loss = 'categorical_crossentropy', optimizer = 'adam', batch = 300, metrics = 'accuracy', epochs = 500, verbose = 0, patience = 10)

generate text using the phrase

pipeline.predict('hello love', word_length = 200, segment = True)

plot loss and accuracy

pipeline.plot_loss_accuracy()

Hyper parameter optimization

Tune your model to know the best optimizer, activation method to use.

pipeline.hyper_params(epochs = 500)
pipeline.saveModel('model')

use a saved model for prediction

#the corpus is the train text file
ttg.load_model_predict(corpus = corpus, padding_method = 'pre', modelname = '../input/model2/model2textgen.h5', sample_text = 'yo yo', word_length = 100)

Give us a star 🐉

If you want to contribute, take a look at the issues and the Futurework.md file

Contributors

Comments
  • use pipenv for managing dependencies

    use pipenv for managing dependencies

    Consider using (pipenv)[https://pypi.org/project/pipenv/] to pin your dependencies. This would allow contributors to easily reproduce the project without messing up the dependencies and its also good on the long run for maintainability

    opened by paularah 1
  • [Snyk] Security upgrade pillow from 6.2.2 to 8.3.2

    [Snyk] Security upgrade pillow from 6.2.2 to 8.3.2

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- high severity | 661/1000
    Why? Recently disclosed, Has a fix available, CVSS 7.5 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-PILLOW-1319443 | pillow:
    6.2.2 -> 8.3.2
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the effected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic

    opened by snyk-bot 0
  • Read on how to create a simple python library

    Read on how to create a simple python library

    https://towardsdatascience.com/how-to-build-your-first-python-package-6a00b02635c9

    https://medium.com/analytics-vidhya/how-to-create-a-python-library-7d5aea80cc3f

    opened by Emekaborisama 0
  • [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    tensorflow 1.14.0 requires protobuf, which is not installed.
    tensorflow-serving-api 1.12.0 requires protobuf, which is not installed.
    tensorboard 1.14.0 requires protobuf, which is not installed.
    GPyOpt 1.2.6 requires GPy, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 551/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.3 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-WHEEL-3180413 | wheel:
    0.30.0 -> 0.38.0
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by Emekaborisama 0
  • [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    [Snyk] Security upgrade wheel from 0.30.0 to 0.38.0

    This PR was automatically created by Snyk using the credentials of a real user.


    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    tensorflow 1.14.0 requires grpcio, which is not installed.
    tensorflow 1.14.0 requires protobuf, which is not installed.
    tensorboard 1.14.0 requires protobuf, which is not installed.
    tensorboard 1.14.0 requires grpcio, which is not installed.
    parameter-sherpa 1.0.6 requires pymongo, which is not installed.
    parameter-sherpa 1.0.6 requires GPyOpt, which is not installed.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- medium severity | 551/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.3 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-WHEEL-3092128 | wheel:
    0.30.0 -> 0.38.0
    | No | No Known Exploit

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the affected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic


    Learn how to fix vulnerabilities with free interactive lessons:

    🦉 Regular Expression Denial of Service (ReDoS)

    opened by Emekaborisama 0
  • [Snyk] Fix for 23 vulnerabilities

    [Snyk] Fix for 23 vulnerabilities

    Snyk has created this PR to fix one or more vulnerable packages in the `pip` dependencies of this project.

    Changes included in this PR

    • Changes to the following files to upgrade the vulnerable dependencies to a fixed version:
      • requirements.txt
    ⚠️ Warning
    torchvision 0.5.0 requires pillow, which is not installed.
    parameter-sherpa 1.0.6 requires scikit-learn, which is not installed.
    GPy 1.10.0 requires paramz, which is not installed.
    GPy 1.10.0 requires cython, which is not installed.
    GPy 1.10.0 has requirement scipy<1.5.0,>=1.3.0, but you have scipy 1.2.3.
    
    

    Vulnerabilities that will be fixed

    By pinning:

    Severity | Priority Score (*) | Issue | Upgrade | Breaking Change | Exploit Maturity :-------------------------:|-------------------------|:-------------------------|:-------------------------|:-------------------------|:------------------------- high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-1055461 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-1055462 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 509/1000
    Why? Has a fix available, CVSS 5.9 | Out-of-bounds Write
    SNYK-PYTHON-PILLOW-1059090 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-1080635 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-PILLOW-1080654 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1081494 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1081501 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1081502 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 654/1000
    Why? Has a fix available, CVSS 8.8 | Heap-based Buffer Overflow
    SNYK-PYTHON-PILLOW-1082329 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Insufficient Validation
    SNYK-PYTHON-PILLOW-1082750 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1090584 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1090586 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1090587 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Denial of Service (DoS)
    SNYK-PYTHON-PILLOW-1090588 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-1292150 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit high severity | 589/1000
    Why? Has a fix available, CVSS 7.5 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-1292151 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 566/1000
    Why? Recently disclosed, Has a fix available, CVSS 5.6 | Buffer Overflow
    SNYK-PYTHON-PILLOW-1316216 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 414/1000
    Why? Has a fix available, CVSS 4 | Out-of-Bounds
    SNYK-PYTHON-PILLOW-574573 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 414/1000
    Why? Has a fix available, CVSS 4 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-574574 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 414/1000
    Why? Has a fix available, CVSS 4 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-574575 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 414/1000
    Why? Has a fix available, CVSS 4 | Out-of-bounds Read
    SNYK-PYTHON-PILLOW-574576 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit medium severity | 469/1000
    Why? Has a fix available, CVSS 5.1 | Buffer Overflow
    SNYK-PYTHON-PILLOW-574577 | pillow:
    6.2.2 -> 8.1.0
    | No | No Known Exploit low severity | 506/1000
    Why? Proof of Concept exploit, Has a fix available, CVSS 3.7 | Regular Expression Denial of Service (ReDoS)
    SNYK-PYTHON-SCIKITLEARN-1079100 | scikit-learn:
    0.20.4 -> 0.24.2
    | No | Proof of Concept

    (*) Note that the real score may have changed since the PR was raised.

    Some vulnerabilities couldn't be fully fixed and so Snyk will still find them when the project is tested again. This may be because the vulnerability existed within more than one direct dependency, but not all of the effected dependencies could be upgraded.

    Check the changes in this PR to ensure they won't cause issues with your project.


    Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open fix PRs.

    For more information: 🧐 View latest project report

    🛠 Adjust project settings

    📚 Read more about Snyk's upgrade and patch logic

    opened by snyk-bot 0
Releases(v1.9.0)
Owner
Emeka boris ama
Machine Learning Engineer, Data Scientist, Youtuber and Advocacy
Emeka boris ama
Switch spaces for knowledge graph embeddings

SwisE Switch spaces for knowledge graph embeddings. Requirements: python3 pytorch numpy tqdm Reproduce the results To reproduce the reported results,

Shuai Zhang 4 Dec 01, 2021
🧪 Cutting-edge experimental spaCy components and features

spacy-experimental: Cutting-edge experimental spaCy components and features This package includes experimental components and features for spaCy v3.x,

Explosion 65 Dec 30, 2022
This is the offline-training-pipeline for our project.

offline-training-pipeline This is the offline-training-pipeline for our project. We adopt the offline training and online prediction Machine Learning

0 Apr 22, 2022
Findings of ACL 2021

Assessing Dialogue Systems with Distribution Distances [arXiv][code] We propose to measure the performance of a dialogue system by computing the distr

Yahui Liu 16 Feb 24, 2022
What are the best Systems? New Perspectives on NLP Benchmarking

What are the best Systems? New Perspectives on NLP Benchmarking In Machine Learning, a benchmark refers to an ensemble of datasets associated with one

Pierre Colombo 12 Nov 03, 2022
A very simple framework for state-of-the-art Natural Language Processing (NLP)

A very simple framework for state-of-the-art NLP. Developed by Humboldt University of Berlin and friends. IMPORTANT: (30.08.2020) We moved our models

flair 12.3k Dec 31, 2022
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS)

Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS) Yoonhyung Lee, Joongbo Shin, Kyomin Jung Abstract: Although early

LEE YOON HYUNG 147 Dec 05, 2022
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

Keon Lee 67 Nov 14, 2022
DataCLUE: 国内首个以数据为中心的AI测评(含模型分析报告)

DataCLUE 以数据为中心的AI测评(DataCLUE) DataCLUE: A Chinese Data-centric Language Evaluation Benchmark 内容导引 章节 描述 简介 介绍以数据为中心的AI测评(DataCLUE)的背景 任务描述 任务描述 实验结果

CLUE benchmark 135 Dec 22, 2022
TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset.

TunBERT is the first release of a pre-trained BERT model for the Tunisian dialect using a Tunisian Common-Crawl-based dataset. TunBERT was applied to three NLP downstream tasks: Sentiment Analysis (S

InstaDeep Ltd 72 Dec 09, 2022
DANeS is an open-source E-newspaper dataset by collaboration between DATASET JSC (dataset.vn) and AIV Group (aivgroup.vn)

DANeS - Open-source E-newspaper dataset Source: Technology vector created by macrovector - www.freepik.com. DANeS is an open-source E-newspaper datase

DATASET .JSC 64 Aug 17, 2022
Creating a Feed of MISP Events from ThreatFox (by abuse.ch)

ThreatFox2Misp Creating a Feed of MISP Events from ThreatFox (by abuse.ch) What will it do? This will fetch IOCs from ThreatFox by Abuse.ch, convert t

17 Nov 22, 2022
Implementaion of our ACL 2022 paper Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation

Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the

hezw.tkcw 20 Dec 12, 2022
This library is testing the ethics of language models by using natural adversarial texts.

prompt2slip This library is testing the ethics of language models by using natural adversarial texts. This tool allows for short and simple code and v

9 Dec 28, 2021
Interpretable Models for NLP using PyTorch

This repo is deprecated. Please find the updated package here. https://github.com/EdGENetworks/anuvada Anuvada: Interpretable Models for NLP using PyT

Sandeep Tammu 19 Dec 17, 2022
A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code or write code yourself

Scriptfab - What is it? A python script to prefab your scripts/text files, and re create them with ease and not have to open your browser to copy code

DevNugget 3 Jul 28, 2021
Reading Wikipedia to Answer Open-Domain Questions

DrQA This is a PyTorch implementation of the DrQA system described in the ACL 2017 paper Reading Wikipedia to Answer Open-Domain Questions. Quick Link

Facebook Research 4.3k Jan 01, 2023
Predict the spans of toxic posts that were responsible for the toxic label of the posts

toxic-spans-detection An attempt at the SemEval 2021 Task 5: Toxic Spans Detection. The Toxic Spans Detection task of SemEval2021 required participant

Ilias Antonopoulos 3 Jul 24, 2022
Image2pcl - Enter the metaverse with 2D image to 3D projections

Image2PCL Enter the metaverse with 2D image to 3D projections! This is an implem

Benjamin Ho 0 Feb 05, 2022
This repository contains helper functions which can help you generate additional data points depending on your NLP task.

NLP Albumentations For Data Augmentation This repository contains helper functions which can help you generate additional data points depending on you

Aflah 6 May 22, 2022