Referências:
texto_simples
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:dream/plain_text')
- Descrição :
DREAM is a multiple-choice Dialogue-based REAding comprehension exaMination dataset. In contrast to existing reading comprehension datasets, DREAM is the first to focus on in-depth multi-turn multi-party dialogue understanding.
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 2041 |
'train' | 6116 |
'validation' | 2040 |
- Características :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"dialogue_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dialogue": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"choice": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Referências:
texto_simples
Use o seguinte comando para carregar este conjunto de dados no TFDS:
ds = tfds.load('huggingface:dream/plain_text')
- Descrição :
DREAM is a multiple-choice Dialogue-based REAding comprehension exaMination dataset. In contrast to existing reading comprehension datasets, DREAM is the first to focus on in-depth multi-turn multi-party dialogue understanding.
- Licença : Nenhuma licença conhecida
- Versão : 1.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'test' | 2041 |
'train' | 6116 |
'validation' | 2040 |
- Características :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"dialogue_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dialogue": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"question": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"choice": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"answer": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}