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Next Word Predictor

by kandikits Updated: Oct 20, 2022


The next word predictor is an exciting feature that helps you type faster on your mobile phone. It predicts the next word in the context you want to type. It is a very useful tool for people who type often and make mistakes while typing. It can be leveraged for auto-suggestion features in messenger and search engine apps.


The next word predictor makes it easy for readers to understand what exactly you are trying for them to read about.

  • Next word predictor is a very useful feature as it increases the readability of your content as well as makes it more understandable for readers.
  • Saves time by reducing the number of typos and grammatical errors in your content.
  • Modify source code to customize as per your requirements.

Deployment Information

The next word predictor created using this kit is added in this section. The entire solution is available as a package to download from the source code repository.


For Windows OS,

  1. Download, extract and double-click the kit installer file to install the kit. Do ensure to extract the zip file before running it.
  2. The installation may take from 2 to 10 minutes based on bandwidth.
  3. After successful installation of the kit, press 'Y' to run the kit and execute cells in the notebook.
  4. To run the kit manually, press 'N' and locate the zip file 'next-word-prediction.zip'
  5. Extract the zip file and navigate to the directory 'next-word-prediction-main'
  6. Open the command prompt in the extracted directory 'next-word-prediction-main' and run the command 'jupyter notebook'


For other Operating System,

  1. Click here to install python
  2. Click here to download the repository
  3. Extract the zip file and navigate to the directory 'next-word-prediction-main'
  4. Open the terminal in the extracted directory 'next-word-prediction-main'
  5. Install dependencies by executing the command 'pip install -r requirements.txt'
  6. Run the command ‘jupyter notebook’ and select the notebook ‘Next Word Predictor.ipynb’ on the browser window.


Click on the button below to download the solution and follow the deployment instructions to begin set-up. This 1-click kit has all the required dependencies and resources you may need to build your Next Word Predictor App.

Instructions to Run

Follow the below instructions to run the solution.

  1. Locate and open the 'Next Word Predictor.ipynb' notebook from the Jupyter Notebook browser window.
  2. Execute cells in the notebook by selecting Cell --> Run All from the Menu bar.
  3. Once all the cells of the notebook are executed, the last interactive cell (Customisation) will be active, there we can give the input data or we can give the input text in the variable 'text_seq' under the variable section.


Input

text_seq = "I'm gonna make him an offer he can't"


Output

['refuse', 'resist', 'take', 'deny', 'get']

Troubleshooting

  1. If you encounter any error related to MS Visual C++, please install MS Visual Build tools
  2. While running batch file, if you encounter Windows protection alert, select More info --> Run anyway.
  3. During kit installer, if you encounter Windows security alert, click Allow.
  4. If you encounter Memory Error, check if the available memory is sufficient and it is proportion to the size of the data being used. For our dataset, the minimum required memory is 8GB.


If your computer doesn't support standard commands from windows 10, you can follow the instructions below to finish the kit installation.

  1. Click here to install python
  2. Click here to download the repository
  3. Extract the zip file and navigate to the directory 'next-word-prediction-main'
  4. Open terminal in the extracted directory 'next-word-prediction-main'
  5. Install dependencies by executing the command 'pip install -r requirements.txt'
  6. Run the command ‘jupyter notebook’ and select the notebook ‘Next Word Predictor.ipynb’ on the browser window.

For a detailed tutorial on installing & executing the solution as well as learning resources including training & certification opportunities, please visit the OpenWeaver Community

Development Environment

VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web-based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers. Jupyter Notebook is used for our development.

jupyterby jupyter

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License: Permissive (BSD-3-Clause)

Jupyter metapackage for installation, docs and chat

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jupyterby jupyter

Python star image 13986 Version:Current License: Permissive (BSD-3-Clause)

Jupyter metapackage for installation, docs and chat
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vscodeby microsoft

TypeScript star image 141766 Version:1.74.3

License: Permissive (MIT)

Visual Studio Code

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vscodeby microsoft

TypeScript star image 141766 Version:1.74.3 License: Permissive (MIT)

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numpyby numpy

Python star image 22526 Version:1.24.1

License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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numpyby numpy

Python star image 22526 Version:1.24.1 License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.
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pandasby pandas-dev

Python star image 36647 Version:1.5.2

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Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 36647 Version:1.5.2 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Text Mining

Libraries in this group are used for analysis and processing of unstructured natural language.

nltkby nltk

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nltkby nltk

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spaCyby explosion

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spaCyby explosion

Python star image 25086 Version:3.4.4 License: Permissive (MIT)

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Machine Learning

The library offers state-of-the-art pre-trained models for Natural Language Processing (NLP).

transformersby huggingface

Python star image 78874 Version:4.25.1

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transformersby huggingface

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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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Kit Solution Source

next-word-predictionby kandi1clickkits

Jupyter Notebook star image 0 Version:v1.0.0

License: Permissive (MIT)

Generative Pretrained Transformer 2 (GPT-2) for Language Modeling using the PyTorch-Transformers library.

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next-word-predictionby kandi1clickkits

Jupyter Notebook star image 0 Version:v1.0.0 License: Permissive (MIT)

Generative Pretrained Transformer 2 (GPT-2) for Language Modeling using the PyTorch-Transformers library.
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Support

If you need help using this kit, you may reach us at the OpenWeaver Community.