claro

Referências:

inat

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/ynat')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 45678
'validation' 9107
  • Características :
{
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 7,
        "names": [
            "IT\uacfc\ud559",
            "\uacbd\uc81c",
            "\uc0ac\ud68c",
            "\uc0dd\ud65c\ubb38\ud654",
            "\uc138\uacc4",
            "\uc2a4\ud3ec\uce20",
            "\uc815\uce58"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

pontos

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/sts')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 11668
'validation' 519
  • Características :
{
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "labels": {
        "label": {
            "dtype": "float64",
            "id": null,
            "_type": "Value"
        },
        "real-label": {
            "dtype": "float64",
            "id": null,
            "_type": "Value"
        },
        "binary-label": {
            "num_classes": 2,
            "names": [
                "negative",
                "positive"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        }
    }
}

nli

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/nli')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 24998
'validation' 3.000
  • Características :
{
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "entailment",
            "neutral",
            "contradiction"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

mais

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/ner')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 21008
'validation' 5.000
  • Características :
{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "tokens": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner_tags": {
        "feature": {
            "num_classes": 13,
            "names": [
                "B-DT",
                "I-DT",
                "B-LC",
                "I-LC",
                "B-OG",
                "I-OG",
                "B-PS",
                "I-PS",
                "B-QT",
                "I-QT",
                "B-TI",
                "I-TI",
                "O"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/re')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 32470
'validation' 7765
  • Características :
{
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "subject_entity": {
        "word": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "start_idx": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "end_idx": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "type": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    },
    "object_entity": {
        "word": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "start_idx": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "end_idx": {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        },
        "type": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    },
    "label": {
        "num_classes": 30,
        "names": [
            "no_relation",
            "org:dissolved",
            "org:founded",
            "org:place_of_headquarters",
            "org:alternate_names",
            "org:member_of",
            "org:members",
            "org:political/religious_affiliation",
            "org:product",
            "org:founded_by",
            "org:top_members/employees",
            "org:number_of_employees/members",
            "per:date_of_birth",
            "per:date_of_death",
            "per:place_of_birth",
            "per:place_of_death",
            "per:place_of_residence",
            "per:origin",
            "per:employee_of",
            "per:schools_attended",
            "per:alternate_names",
            "per:parents",
            "per:children",
            "per:siblings",
            "per:spouse",
            "per:other_family",
            "per:colleagues",
            "per:product",
            "per:religion",
            "per:title"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

DP

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/dp')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 10.000
'validation' 2000
  • Características :
{
    "sentence": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "index": [
        {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        }
    ],
    "word_form": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "lemma": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "pos": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "head": [
        {
            "dtype": "int32",
            "id": null,
            "_type": "Value"
        }
    ],
    "deprel": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

senhor

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/mrc')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 17554
'validation' 5841
  • Características :
{
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "context": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "is_impossible": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    },
    "question_type": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answers": {
        "feature": {
            "answer_start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

ai

Use o seguinte comando para carregar este conjunto de dados no TFDS:

ds = tfds.load('huggingface:klue/wos')
  • Descrição :
KLUE (Korean Language Understanding Evaluation)
Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language
understanding capability of Korean language models. KLUE consists of 8 diverse and representative tasks, which are accessible
to anyone without any restrictions. With ethical considerations in mind, we deliberately design annotation guidelines to obtain
unambiguous annotations for all datasets. Futhermore, we build an evaluation system and carefully choose evaluations metrics
for every task, thus establishing fair comparison across Korean language models.
  • Licença : CC-BY-SA-4.0
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'train' 8.000
'validation' 1000
  • Características :
{
    "guid": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "domains": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "dialogue": [
        {
            "role": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "state": [
                {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                }
            ]
        }
    ]
}