Summarizer Cnndm

🚀 Summarization

A fine - tuned model for text summarization, leveraging the power of the Bart architecture.

🚀 Quick Start

The model is a BartForConditionalGeneration model fine - tuned on 10000 samples from the cnn - dailymail dataset for summarization tasks.

✨ Features

• It is a PyTorch model, which can be easily integrated into existing deep - learning workflows.

📦 Installation

There is no specific installation steps provided in the original document.

💻 Usage Examples

Basic Usage

from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline

tokenizer = AutoTokenizer.from_pretrained("yuvraj/summarizer-cnndm") 
model = AutoModelWithLMHead.from_pretrained("yuvraj/summarizer-cnndm")

summarizer = pipeline('summarization', model=model, tokenizer=tokenizer)
summarizer("<Text to be summarized>")

🔧 Technical Details

The model is a BartForConditionalGeneration model fine - tuned on a subset (10000 samples) of the cnn - dailymail dataset.

📚 Documentation

Limitations and bias

⚠️ Important Note

The model is trained on a small dataset, which may lead to limitations in generalization and potential biases.