Références :
Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :
ds = tfds.load('huggingface:cosmos_qa')
- Description :
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
- Licence : Aucune licence connue
- Version : 0.1.0
- Divisions :
Diviser | Exemples |
---|---|
'test' | 6963 |
'train' | 25262 |
'validation' | 2985 |
- Caractéristiques :
{
"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"
}
}