# T5 Text Summarizer

This repository contains a simple text summarization script using a pre-trained T5 model from the Hugging Face Transformers library. The script demonstrates how to use prompt-based summarization to generate a concise summary of an input text.

## Overview

The main script (`model.py`) defines a function `summarize_text` that:
- Loads the T5 tokenizer and T5 model.
- Adds a summarization prompt (`"summarize: "`) to the input text.
- Tokenizes the input text and truncates it to a maximum length.
- Generates a summary using beam search.
- Decodes the generated token sequence back into human-readable text while skipping special tokens.

## Code Explanation

### Tokenization and Decoding

- **Tokenization:**  
  The input text is first prefixed with the summarization prompt and then tokenized using:
  ```python
  input_ids = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)

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license: apache-2.0
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