/Hugging-Face-Data-Summarization

Hugging Face Data Summarization 🤗

Data Summarization ⌗

This is a NLP technique and it is basically of 2 types:

  • Extractive

    • Easy to achieve
    • Less CPU Consumption
    • NLTK Library

  • Abstractive

    • Difficult to achieve
    • More CPU Consumption
    • Transformers and Pipelines

Transformer Package - Hugging Face

The Hugging Face transformers package is an immensely popular python library provided pre-trained models that are extraordinarly useful for Natural Language Processing(NLP). And it is supported by both PyTorch and Tensorflow

Transformer

  • Transformer : transformer is an algorithm that can change one DataFrame into other DataFrame
  • Pipeline : A pipeline chains multiple transformers and estimators together to estimate an ML workflow
  • Estimator : An estimator is an algorithm that can fit on a DataFrame to produce a transformer

Hugging Face Pipelines

The pipelines are a great and easy way to use models for inference. This pipelines are objects that abstract most of the complex codes from the library offering a simple API dedicated to several tasks

Inference is the process of using a trained machine learning algorithm to make useful predictions