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Automated Text Summarizer

This model is a fine-tuned version of BART-large-cnn, specifically designed to generate high-quality, abstractive summaries of long-form text.

Model Description

Developed by: Aditya Prasad Sahu
Model type: Transformer-based Encoder-Decoder (BART)
Language(s): English
Task: Text Summarization

Project Context

This project was developed as part of my focus on Natural Language Processing (NLP) and Deep Learning. My experience includes a 20-day internship covering CNNs, RNNs, and Transformer models (BERT/GPT), and this summarizer is a practical application of those concepts.

Intended Use

This model is intended for:

Summarizing news articles.
Condensing research papers or long reports.
Integrating into personal portfolio projects as a microservice.

Performance

Framework: PyTorch & Transformers
Precision: Float32
Base Model: facebook/bart-large-cnn

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Safetensors

Model size

0.4B params

Tensor type

F32