References:
abstractive
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:aquamuse/abstractive')
- Description:
AQuaMuSe is a novel scalable approach to automatically mine dual query based multi-document summarization datasets for extractive and abstractive summaries using question answering dataset (Google Natural Questions) and large document corpora (Common Crawl)
- License: No known license
- Version: 2.3.0
- Splits:
| Split | Examples |
|---|---|
'test' |
811 |
'train' |
6253 |
'validation' |
661 |
- Features:
{
"query": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"input_urls": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
extractive
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:aquamuse/extractive')
- Description:
AQuaMuSe is a novel scalable approach to automatically mine dual query based multi-document summarization datasets for extractive and abstractive summaries using question answering dataset (Google Natural Questions) and large document corpora (Common Crawl)
- License: No known license
- Version: 2.3.0
- Splits:
| Split | Examples |
|---|---|
'test' |
811 |
'train' |
6253 |
'validation' |
661 |
- Features:
{
"query": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"input_urls": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}