README.md

---
pipeline_tag: summarization
datasets:
- samsum
language:
- en
metrics:
- rouge
library_name: transformers
widget:
- text: | 
    John: Hey! I've been thinking about getting a PlayStation 5. Do you think it is worth it? 
    Dan: Idk man. R u sure ur going to have enough free time to play it? 
    John: Yeah, that's why I'm not sure if I should buy one or not. I've been working so much lately idk if I'm gonna be able to play it as much as I'd like.
- text: | 
    Sarah: Do you think it's a good idea to invest in Bitcoin?
    Emily: I'm skeptical. The market is very volatile, and you could lose money.
    Sarah: True. But there's also a high upside, right?
- text: | 
    Madison: Hello Lawrence are you through with the article?
    Lawrence: Not yet sir.
    Lawrence: But i will be in a few.
    Madison: Okay. But make it quick.
    Madison: The piece is needed by today
    Lawrence: Sure thing
    Lawrence: I will get back to you once i am through."

---

# Description

This model is a specialized adaptation of the <b>facebook/bart-large-xsum</b>, fine-tuned for enhanced performance on dialogue summarization using the <b>SamSum</b> dataset.

## Development
- Kaggle Notebook: [Text Summarization with Large Language Models](https://www.kaggle.com/code/lusfernandotorres/text-summarization-with-large-language-models)

## Usage

```python

from transformers import pipeline

model = pipeline("summarization", model="luisotorres/bart-finetuned-samsum")

conversation = '''Sarah: Do you think it's a good idea to invest in Bitcoin?
    Emily: I'm skeptical. The market is very volatile, and you could lose money.
    Sarah: True. But there's also a high upside, right?                                     
'''
model(conversation)
```