klue

Referencje:

• Kod
• Przytulająca twarz

ynat

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/ynat')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
    }
}

st

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/sts')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
        }
    }
}

nie

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/nli')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
    }
}

nie

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/ner')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
    }
}

Odnośnie

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/re')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/dp')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
        }
    ]
}

pan

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/mrc')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
    }
}

wos

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:klue/wos')

• Opis :

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.

• Licencja : CC-BY-SA-4.0
• Wersja : 1.0.0
• Podziały :

• Cechy :

{
    "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"
                }
            ]
        }
    ]
}