This Project contains two API one is auto-corrections and other is autosuggestions. Auto-correction build with the help of text blob library and other one is auto-suggestions with the help of transforms and Bart large model.
The purpose of this project is to train the next word predicting models. Models should be able to suggest the next word after the user has input word/words auto-correct the incorrect word/s. Autocorrect the incorrect word in the input field like Gmail and Grammarly doing.
- Language Prediction
- Natural Language Processing
- Transformers Bart Model
- Textblob
- Python
- Python Flask
- Torch, Transforms
- JS, HTML
app.py
- In that file three APIs are there, one is auto_correction and the second one is auto_suggestion and the last one is index file rendering file.main.py
- use pre-trained Bart model for next word prediction
- Frontend Development
- Data Collection
- Data Processing/Cleaning
- Words Tokenizing
- Model Training
- Demo Development
-
Create a python virtual environment via command
virtualenv correctme_env -p python3
-
Install python dependencies via command
pip3 install -r requirement.txt
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Start server via command
python3 app.py
. -
Open your browser at http://127.0.0.1:8083/
- Deepak Chawla - Linkedin
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This project is licensed under the MIT License - see the LICENSE.md file for details
- Hat tip to anyone who’s code was used
- Inspiration