Friday, 25 March 2022

Hugging Face Introduction

 Hugging face provides libraries for Natural Language Processing (NLP) using transformers. Hugging face can be use for following tasks

  • Sentiment Analysis - Provides the score in terms of positive and negative
  • Zero Shot Classification-It classifies a text into the mention topics by allocating percentage to each topic.
  • Text Generation - Generates the summary basis on short text passed
  • Mask Filling-If a word is hidden in a string, this method is used for prediction of the word
  • Named Entity Recognition-It classifies the entities into predefined categories such as organization, locations, quantities, etc.
  • Question Answering - Basis on the context passed in pipeline, this feature answers the questions
  • Summarization - It summarizes the long text into short summary
  • Translation - Translates the text from one language to other

 

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