Meeting Summary Samsum

🚀 bart-large-xsum-samsum

bart-large-xsum-samsum 模型基於序列到序列（seq2seq）架構，利用 BART 模型進行抽象文本摘要任務，可有效處理對話數據的摘要生成，在 SAMSum 數據集上表現出色。

🚀 快速開始

本模型是在 Samsum 數據集上對 facebook/bart-large-xsum 進行微調得到的。

💻 使用示例

基礎用法

from transformers import pipeline
summarizer = pipeline("summarization", model="knkarthick/bart-large-xsum-samsum")
conversation = '''Hannah: Hey, do you have Betty's number?
Amanda: Lemme check
Amanda: Sorry, can't find it.
Amanda: Ask Larry
Amanda: He called her last time we were at the park together
Hannah: I don't know him well
Amanda: Don't be shy, he's very nice
Hannah: If you say so..
Hannah: I'd rather you texted him
Amanda: Just text him 🙂
Hannah: Urgh.. Alright
Hannah: Bye
Amanda: Bye bye                                       
'''
summarizer(conversation)

📚 詳細文檔

模型信息

評估指標

該模型在 SAMSum 數據集上的評估指標如下：

示例對話

Hannah: Hey, do you have Betty's number?
Amanda: Lemme check
Amanda: Sorry, can't find it.
Amanda: Ask Larry
Amanda: He called her last time we were at the park together
Hannah: I don't know him well
Amanda: Don't be shy, he's very nice
Hannah: If you say so..
Hannah: I'd rather you texted him
Amanda: Just text him 🙂
Hannah: Urgh.. Alright
Hannah: Bye
Amanda: Bye bye

📄 許可證

本模型使用 Apache 2.0 許可證。