Ahmed766/nlp-pipeline-demo

NLP Pipeline

This pipeline performs multiple NLP tasks including tokenization, named entity recognition, part-of-speech tagging, and text summarization.

Features

• Named Entity Recognition (NER)
• Part-of-Speech (POS) tagging
• Text summarization
• Tokenization
• Sentiment analysis
• Language detection

Usage

from nlp_pipeline import NLPPipeline

pipeline = NLPPipeline()
text = "Apple Inc. is an American multinational technology company headquartered in Cupertino, California."
result = pipeline.process(text)
print(result)

Model Details

• Architecture: spaCy small model + BART for summarization
• Components: NER, POS, Dependency parsing
• Languages: English (can be extended)

Hugging Face Space

This model can be deployed as a Hugging Face Space with a Gradio interface for easy interaction.

Installation

pip install -r requirements.txt
python -m spacy download en_core_web_sm

Local Testing

python test_pipeline.py