Referencias:
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:cosmos_qa')
- Descripción :
Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
- Licencia : Sin licencia conocida
- Versión : 0.1.0
- Divisiones :
Separar | Ejemplos |
---|---|
'test' | 6963 |
'train' | 25262 |
'validation' | 2985 |
- Características :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"context": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer0": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"answer3": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}