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README.md

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+
+---
+displayName: SAMSum Corpus
+labelTypes:
+- Classification
+license:
+- CC BY-NC-ND 4.0
+mediaTypes:
+- Text
+paperUrl: https://arxiv.org/pdf/1911.12237v2.pdf
+publishDate: "2019"
+publishUrl: https://github.com/huggingface/datasets/tree/master/datasets/samsum
+publisher:
+- Samsung R&D Institute Poland
+tags:
+- Text
+taskTypes:
+- Text Summarization/Simplication
+- Federated Learning
+- Abstractive Text Summarization
+
+---
+# 数据集介绍
+  ## 简介
+   SAMSum 数据集包含大约 16k 个带有摘要的类似信使的对话。对话由精通英语的语言学家创建和记录。语言学家被要求创建类似于他们每天所写的对话，以反映他们现实生活中的信使对话的主题比例。风格和语域是多样化的——对话可以是非正式的、半正式的或正式的，它们可能包含俚语、表情符号和错别字。然后，用摘要对对话进行注释。假设摘要应该是人们在第三人称对话中所谈论内容的简明扼要。 SAMSum 数据集由波兰三星研发研究所准备并分发用于研究目的（非商业许可：CC BY-NC-ND 4.0）。 
+  ## 引文
+  
+```
+"@article{gliwa2019samsum,
+title={SAMSum corpus: A human-annotated dialogue dataset for abstractive summarization},
+author={Gliwa, Bogdan and Mochol, Iwona and Biesek, Maciej and Wawer, Aleksander},
+journal={arXiv preprint arXiv:1911.12237},
+year={2019}
+}"
+```
+
+  
+## Download dataset
+:modelscope-code[]{type="git"}

dataset-samsum-corpus

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metafile.yaml

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+displayName: SAMSum Corpus
+labelTypes:
+- Classification
+license:
+- CC BY-NC-ND 4.0
+mediaTypes:
+- Text
+paperUrl: https://arxiv.org/pdf/1911.12237v2.pdf
+publishDate: "2019"
+publishUrl: https://github.com/huggingface/datasets/tree/master/datasets/samsum
+publisher:
+- Samsung R&D Institute Poland
+tags:
+- Text
+taskTypes:
+- Text Summarization/Simplication
+- Federated Learning
+- Abstractive Text Summarization

quickstart.md

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+
+## SDK usage
+```python
+from modelscope.msdatasets import MsDataset
+
+MsDataset.load("OpenDataLab/SAMSum_Corpus")
+
+# Note: If the SDK is not available, please use git to download the dataset.
+```