You can deploy this model and start earning money today!

sjasmeet/
pegsus-text-summarization

Name: pegsus-text-summarization
Availability: InStock

pytorch

pegasus

google/pegasus-cnn_dailymail

finetune

apache-2.0

Views

No views yet

Pegasus-based Text Summarization Model

Model Name: pegsus-text-summarization

Model Description

This model is a fine-tuned version of the Pegasus model, specifically adapted for the task of text summarization. It is trained on the SAMSum dataset, which is designed for summarizing conversations.

Usage

This model can be used to generate concise summaries of input text, particularly for conversational text or dialogue-based inputs.

How to Use

You can use this model with the Hugging Face transformers library. Below is an example code snippet:

bash

from transformers import PegasusForConditionalGeneration, PegasusTokenizer

# Load the pre-trained model and tokenizer
model_name = "ailm/pegsus-text-summarization"
model = PegasusForConditionalGeneration.from_pretrained(model_name)
tokenizer = PegasusTokenizer.from_pretrained(model_name)

# Define the input text
text = "Your input text here"

# Tokenize the input text
tokens = tokenizer(text, truncation=True, padding="longest", return_tensors="pt")

# Generate the summary
summary = model.generate(**tokens)

# Decode and print the summary
print(tokenizer.decode(summary[0], skip_special_tokens=True))

sjasmeet/pegsus-text-summarization

Pegasus-based Text Summarization Model

Model Description

Usage

How to Use

sjasmeet/
pegsus-text-summarization