samandar1105/text-summarizer

T5-small Fine-Tuned on CNN/DailyMail

This model generates abstractive summaries of English news articles.

Model Details

• —Base model: t5-small
• —Dataset: CNN/DailyMail v3.0.0
• —Task: Abstractive text summarization
• —Framework: PyTorch + HuggingFace Transformers

Performance (ROUGE, on held-out test sample)

How to Use

⚠️ This model requires the "summarize: " prefix on every input, since it's a T5 model.

from transformers import pipeline

summarizer = pipeline("summarization", model="samandar1105/text-summarizer")
text = "summarize: " + "YOUR LONG ARTICLE TEXT HERE"
result = summarizer(text, max_length=80, min_length=20, do_sample=False)
print(result[0]["summary_text"])

Training Details

• —Learning rate: 3e-5
• —Epochs: 4
• —Batch size: 8
• —Max input length: 512 tokens
• —Max target length: 128 tokens