xpegamento

Referencias:

ner

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/ner')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 3007
'test.en' 3454
'test.es' 1523
'test.nl' 5202
'train' 14042
'validation.de' 2874
'validation.en' 3252
'validation.es' 1923
'validation.nl' 2895
  • Características :
{
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "ner": {
        "feature": {
            "num_classes": 9,
            "names": [
                "O",
                "B-PER",
                "I-PER",
                "B-ORG",
                "I-ORG",
                "B-LOC",
                "I-LOC",
                "B-MISC",
                "I-MISC"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

posición

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/pos')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.ar' 679
'test.bg' 1115
'test.de' 976
'test.el' 455
'test.en' 2076
'test.es' 425
'test.fr' 415
'test.hi' 1683
'test.it' 481
'test.nl' 595
'test.pl' 2214
'test.ru' 600
'test.th' 497
'test.tr' 982
'test.ur' 534
'test.vi' 799
'test.zh' 499
'train' 25376
'validation.ar' 908
'validation.bg' 1114
'validation.de' 798
'validation.el' 402
'validation.en' 2001
'validation.es' 1399
'validation.fr' 1475
'validation.hi' 1658
'validation.it' 563
'validation.nl' 717
'validation.pl' 2214
'validation.ru' 578
'validation.th' 497
'validation.tr' 987
'validation.ur' 551
'validation.vi' 799
'validation.zh' 499
  • Características :
{
    "words": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "pos": {
        "feature": {
            "num_classes": 17,
            "names": [
                "ADJ",
                "ADP",
                "ADV",
                "AUX",
                "CCONJ",
                "DET",
                "INTJ",
                "NOUN",
                "NUM",
                "PART",
                "PRON",
                "PROPN",
                "PUNCT",
                "SCONJ",
                "SYM",
                "VERB",
                "X"
            ],
            "names_file": null,
            "id": null,
            "_type": "ClassLabel"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}

mlqa

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/mlqa')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.ar' 5335
'test.de' 4517
'test.en' 11590
'test.es' 5253
'test.hi' 4918
'test.vi' 5495
'test.zh' 5137
'train' 87599
'validation.ar' 517
'validation.de' 512
'validation.en' 1148
'validation.es' 500
'validation.hi' 507
'validation.vi' 511
'validation.zh' 504
  • Características :
{
    "context": {
        "dtype": "string",
        "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"
    }
}

Carolina del Norte

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/nc')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.ru' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.ru' 10000
  • Características :
{
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_category": {
        "num_classes": 10,
        "names": [
            "foodanddrink",
            "sports",
            "travel",
            "finance",
            "lifestyle",
            "news",
            "entertainment",
            "health",
            "video",
            "autos"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

xnli

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/xnli')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.ar' 5010
'test.bg' 5010
'test.de' 5010
'test.el' 5010
'test.en' 5010
'test.es' 5010
'test.fr' 5010
'test.hi' 5010
'test.ru' 5010
'test.sw' 5010
'test.th' 5010
'test.tr' 5010
'test.ur' 5010
'test.vi' 5010
'test.zh' 5010
'train' 392702
'validation.ar' 2490
'validation.bg' 2490
'validation.de' 2490
'validation.el' 2490
'validation.en' 2490
'validation.es' 2490
'validation.fr' 2490
'validation.hi' 2490
'validation.ru' 2490
'validation.sw' 2490
'validation.th' 2490
'validation.tr' 2490
'validation.ur' 2490
'validation.vi' 2490
'validation.zh' 2490
  • Características :
{
    "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"
    }
}

patas-x

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/paws-x')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 2000
'test.en' 2000
'test.es' 2000
'test.fr' 2000
'train' 49401
'validation.de' 2000
'validation.en' 2000
'validation.es' 2000
'validation.fr' 2000
  • Características :
{
    "sentence1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "different",
            "same"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

qadsm

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/qadsm')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 10000
'test.en' 10000
'test.fr' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.fr' 10000
  • Características :
{
    "query": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ad_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "ad_description": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "relevance_label": {
        "num_classes": 2,
        "names": [
            "Bad",
            "Good"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

wpr

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/wpr')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 9997
'test.en' 10004
'test.es' 10006
'test.fr' 10020
'test.it' 10001
'test.pt' 10015
'test.zh' 9999
'train' 99997
'validation.de' 10004
'validation.en' 10008
'validation.es' 10004
'validation.fr' 10005
'validation.it' 10003
'validation.pt' 10001
'validation.zh' 10002
  • Características :
{
    "query": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "web_page_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "web_page_snippet": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "relavance_label": {
        "num_classes": 5,
        "names": [
            "Bad",
            "Fair",
            "Good",
            "Excellent",
            "Perfect"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

qam

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/qam')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 10000
'test.en' 10000
'test.fr' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.fr' 10000
  • Características :
{
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "False",
            "True"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

q g

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/qg')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.it' 10000
'test.pt' 10000
'train' 100000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.it' 10000
'validation.pt' 10000
  • Características :
{
    "answer_passage": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ntg

Utilice el siguiente comando para cargar este conjunto de datos en TFDS:

ds = tfds.load('huggingface:xglue/ntg')
  • Descripción :
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained
models with respect to cross-lingual natural language understanding and generation.
The benchmark is composed of the following 11 tasks:
- NER
- POS Tagging (POS)
- News Classification (NC)
- MLQA
- XNLI
- PAWS-X
- Query-Ad Matching (QADSM)
- Web Page Ranking (WPR)
- QA Matching (QAM)
- Question Generation (QG)
- News Title Generation (NTG)

For more information, please take a look at https://microsoft.github.io/XGLUE/.
  • Licencia : Sin licencia conocida
  • Versión : 1.0.0
  • Divisiones :
Separar Ejemplos
'test.de' 10000
'test.en' 10000
'test.es' 10000
'test.fr' 10000
'test.ru' 10000
'train' 300000
'validation.de' 10000
'validation.en' 10000
'validation.es' 10000
'validation.fr' 10000
'validation.ru' 10000
  • Características :
{
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}