azureml-acft-contrib-hf-nlp

Create a mini-application called 'AzureML NLP Text Classifier' using the Python package 'azureml-acft-contrib-hf-nlp'. This application will serve as a text classification tool that leverages pre-trained models from Hugging Face to classify text into predefined categories. The application should include the following functionalities:

1. User Interface: Develop a simple command-line interface (CLI) that allows users to input text and select a pre-trained model from a list of available models provided by Hugging Face.
2. Model Selection: Implement functionality within the CLI to allow users to choose from different types of models such as sentiment analysis, topic classification, etc., based on their needs.
3. Text Classification: Use the 'azureml-acft-contrib-hf-nlp' package to load and utilize selected pre-trained models for classifying the user-provided text. Ensure that the package is integrated smoothly to handle model loading and prediction processes efficiently.
4. Result Presentation: Display the classification results clearly to the user, including the predicted category and confidence scores if applicable.
5. Documentation: Provide comprehensive documentation on how to install dependencies, run the application, and interpret the results.
6. Optional Features: Consider adding optional features like saving the classified text and its result to a local file or database, or allowing users to upload text files directly instead of typing them in manually.

This project aims to demonstrate the practical use of 'azureml-acft-contrib-hf-nlp' in building a real-world application, showcasing its capabilities in natural language processing tasks.