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Text Classification Notebook

Logo for Text Classification Notebook
Description
End to End sample workflow for Text Classification starting with training in TLT and deployment using Jarvis.
Publisher
NVIDIA
Latest Version
v1.0
Modified
April 4, 2023
Compressed Size
43.54 KB

Text Classification

Text Classification is one of the most common tasks in NLP, which is the process of categorizing the text into a group of words. By using NLP, text classification can automatically analyze text and then assign a set of predefined tags or categories based on its context. It is applied in a wide variety of applications, including sentiment analysis, spam filtering, news categorization, domain/intent detection for dialogue systems, etc.

The best place to get started with TLT - Text Classification would be the TLT - Text Classification jupyter notebooks. This resource has two notebooks included.

  1. Training: Sample workflow for training a text classification model and export the model to a .ejrvs file
  2. Deployment: Sample workflow to consume the .ejrvs file and deploy it to Jarvis.

If you are a seasoned Conversation AI developer we recommend installing TLT and referring to the TLT documentation for usage information.

Pre-Requisites

Please make sure to install the following before proceeding further:

  • python 3.6.9
  • docker-ce > 19.03.5
  • docker-API 1.40
  • nvidia-container-toolkit > 1.3.0-1
  • nvidia-container-runtime > 3.4.0-1
  • nvidia-docker2 > 2.5.0-1
  • nvidia-driver >= 455.23

Note: A compatible NVIDIA GPU would be required.

Installation

We recommend that you install TLT inside a virtual environment. The steps to do the same are as follows

virtualenv -p python3 <name of venv>
source <name of venv>/bin/activate
pip install jupyter notebook # If you need to run the notebooks

TLT is python package that is hosted in nvidia python package index. You may install by using python’s package manager, pip.

pip install nvidia-pyindex
pip install nvidia-tlt

To download the jupyter notebook please:

  1. Download the samples using the ngc cli with the following command
ngc registry resource download-version "nvidia/tlt-jarvis/textclassification_notebook:v1.0"
  1. Instantiate the jupyter notebook server
jupyter notebook --ip 0.0.0.0 --allow-root --port 8888

License

By downloading and using the models and resources packaged with TLT Conversational AI, you would be accepting the terms of the Jarvis license