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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