Pegasus X Sumstew

🚀 Pegasus-x-sumstew

Pegasus-x-sumstew是基于Pegasus-x-large模型微调得到的，可对长文本进行抽象概括，生成简洁且准确的摘要。

🚀 快速开始

你可以使用transformers库中的pipeline函数来使用此模型：

from transformers import pipeline

summarizer = pipeline("summarization", "joemgu/pegasus-x-sumstew")
text = "Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, 'and what is the use of a book,' thought Alice 'without pictures or conversations?' So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her. There was nothing so very remarkable in that; nor did Alice think it so very much out of the way to hear the Rabbit say to itself, 'Oh dear! Oh dear! I shall be late!' (when she thought it over afterwards, it occurred to her that she ought to have wondered at this, but at the time it all seemed quite natural); but when the Rabbit actually took a watch out of its waistcoat-pocket, and looked at it, and then hurried on, Alice started to her feet, for it flashed across her mind that she had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it, and fortunately was just in time to see it pop down a large rabbit-hole under the hedge. In another moment down went Alice after it, never once considering how in the world she was to get out again."
summary = summarizer(text,
                     num_beams=8,
                     repetition_penalty=3.5,
                     no_repeat_ngram_size=4,
                     encoder_no_repeat_ngram_size=4
    )[0]["summary_text"]
print(summary)

输出：

Alice is a bored and curious girl who follows a White Rabbit with a watch into a rabbit-hole. She enters a strange world where she has many adventures and meets many peculiar creatures.

✨ 主要特性

• 可对英文长文本进行抽象概括，生成摘要。
• 适用于学术记录、会议纪要、文学作品等长文本的摘要生成。

📦 安装指南

文档未提及安装步骤，故跳过此章节。

💻 使用示例

基础用法

from transformers import pipeline

summarizer = pipeline("summarization", "joemgu/pegasus-x-sumstew")
text = "Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, 'and what is the use of a book,' thought Alice 'without pictures or conversations?' So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her. There was nothing so very remarkable in that; nor did Alice think it so very much out of the way to hear the Rabbit say to itself, 'Oh dear! Oh dear! I shall be late!' (when she thought it over afterwards, it occurred to her that she ought to have wondered at this, but at the time it all seemed quite natural); but when the Rabbit actually took a watch out of its waistcoat-pocket, and looked at it, and then hurried on, Alice started to her feet, for it flashed across her mind that she had never before seen a rabbit with either a waistcoat-pocket, or a watch to take out of it, and burning with curiosity, she ran across the field after it, and fortunately was just in time to see it pop down a large rabbit-hole under the hedge. In another moment down went Alice after it, never once considering how in the world she was to get out again."
summary = summarizer(text,
                     num_beams=8,
                     repetition_penalty=3.5,
                     no_repeat_ngram_size=4,
                     encoder_no_repeat_ngram_size=4
    )[0]["summary_text"]
print(summary)

高级用法

文档未提及高级用法代码示例，故跳过此部分。

📚 详细文档

模型描述

此模型是Pegasus-x-large模型在CNN-Dailymail、Samsum、Booksum和Laysum数据集的过滤子集上进行微调得到的版本。它可以生成长文本的抽象摘要。

预期用途与限制

该模型可用于对英文长文本进行摘要生成，例如学术记录、会议纪要或文学作品。但它不适用于对短文本（如推文、标题或说明文字）进行摘要。如果输入文本包含事实错误、俚语或冒犯性语言，模型可能会生成不准确或有偏差的摘要。

训练数据

该模型在CNN-Dailymail、Samsum、Booksum和Laysum数据集的过滤子集上进行了微调。这些数据集包含各种类型的文本及其抽象摘要。筛选出的子集仅包含长度超过1000个单词且摘要长度少于100个单词的文本。该子集的总大小约为15万个示例。

局限性和偏差

该模型可能继承了预训练的Pegasus-x-large模型和微调数据集的一些局限性和偏差。一些可能的偏差来源包括：

• 预训练的Pegasus-x-large模型是在来自各种来源的大量英文文本语料库上进行训练的，这可能无法反映不同语言和文化的多样性和细微差别。
• 微调数据集是从不同的领域和体裁收集的，它们可能有自己的文体惯例以及对某些主题和事件的观点。
• 微调数据集仅包含抽象摘要，这可能无法捕捉原始文本的所有重要信息和细微差别。
• 微调数据集仅涵盖了特定时间段和来源的文本，这可能无法反映当前的情况和趋势。

因此，用户在使用此模型时应意识到这些局限性和偏差，并评估其性能和对特定用例的适用性。

🔧 技术细节

文档未提供具体技术细节（说明内容少于50字），故跳过此章节。

📄 许可证

该模型使用Apache-2.0许可证。