cola

Referências:

ner

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

ds = tfds.load('huggingface:xglue/ner')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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"
    }
}

posição

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

ds = tfds.load('huggingface:xglue/pos')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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

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

ds = tfds.load('huggingface:xglue/mlqa')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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"
    }
}

nc

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

ds = tfds.load('huggingface:xglue/nc')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test.de' 10.000
'test.en' 10.000
'test.es' 10.000
'test.fr' 10.000
'test.ru' 10.000
'train' 100.000
'validation.de' 10.000
'validation.en' 10.000
'validation.es' 10.000
'validation.fr' 10.000
'validation.ru' 10.000
  • 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

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

ds = tfds.load('huggingface:xglue/xnli')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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

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

ds = tfds.load('huggingface:xglue/paws-x')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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

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

ds = tfds.load('huggingface:xglue/qadsm')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test.de' 10.000
'test.en' 10.000
'test.fr' 10.000
'train' 100.000
'validation.de' 10.000
'validation.en' 10.000
'validation.fr' 10.000
  • 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

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

ds = tfds.load('huggingface:xglue/wpr')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'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

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

ds = tfds.load('huggingface:xglue/qam')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test.de' 10.000
'test.en' 10.000
'test.fr' 10.000
'train' 100.000
'validation.de' 10.000
'validation.en' 10.000
'validation.fr' 10.000
  • 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"
    }
}

qg

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

ds = tfds.load('huggingface:xglue/qg')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test.de' 10.000
'test.en' 10.000
'test.es' 10.000
'test.fr' 10.000
'test.it' 10.000
'test.pt' 10.000
'train' 100.000
'validation.de' 10.000
'validation.en' 10.000
'validation.es' 10.000
'validation.fr' 10.000
'validation.it' 10.000
'validation.pt' 10.000
  • Características :
{
    "answer_passage": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ntg

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

ds = tfds.load('huggingface:xglue/ntg')
  • Descrição :
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/.
  • Licença : Nenhuma licença conhecida
  • Versão : 1.0.0
  • Divisões :
Dividir Exemplos
'test.de' 10.000
'test.en' 10.000
'test.es' 10.000
'test.fr' 10.000
'test.ru' 10.000
'train' 300000
'validation.de' 10.000
'validation.en' 10.000
'validation.es' 10.000
'validation.fr' 10.000
'validation.ru' 10.000
  • Características :
{
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}