קלוע

הפניות:

• קוד
• מחבקת פנים

ynat

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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"
    }
}

sts

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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"
    }
}

ner

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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"
    }
}

מִחָדָשׁ

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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"
        }
    ]
}

mrc

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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

השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:

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

• תיאור :

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.

• רישיון : CC-BY-SA-4.0
• גרסה : 1.0.0
• פיצולים :

• תכונות :

{
    "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"
                }
            ]
        }
    ]
}