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ISA course: ML/DL deployment - Text data type

Example of text classification inference. You can send your messaged either by clicking on the "Send" button or pressing "Enter".

Author(s):

  • Matej Volansky (2024)
  • as a part of the team work preparation in 2023/2024

Docker image size: 578 MB ( build takes quite some time )

File the model was trained from: IAU_072_sentiment_analysis_in_text.ipynb

Setup

First train your model and save the .pkl state dictionary after training (considering you're using NLTK + Pickle).

Run

To use this inference, just run

docker compose up

After successful build, your server will be available at http://localhost:8080/

For manual running without docker you have to create a python virtual environment.

python -m venv venv

source venv/bin/activate          # on Linux based distros
source venv\Scripts\activate.ps1  # on Windows (Powershell)
source venv\Scripts\activate.bat  # on Windows (cmd)

Install the required libraries via this command

pip install -r requirements.txt

Install these nltk packages via python

import nltk
nltk.download('stopwords')
nltk.download('punkt') 
nltk.download('averaged_perceptron_tagger') 
nltk.download('wordnet')

you must not move the nltk\data directories afterwards.