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.
.ejrvsfile 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.
Please make sure to install the following before proceeding further:
Note: A compatible NVIDIA GPU would be required.
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:
ngc registry resource download-version "nvidia/tlt-jarvis/textclassification_notebook:v1.0"
jupyter notebook --ip 0.0.0.0 --allow-root --port 8888
By downloading and using the models and resources packaged with TLT Conversational AI, you would be accepting the terms of the Jarvis license