lem x

Referensi:

tidak

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/ner')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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"
    }
}

pos

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/pos')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/mlqa')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/nc')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/xnli')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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"
    }
}

cakar-x

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/paws-x')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/qadsm')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/wpr')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/qam')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "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

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/qg')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur : 
{
    "answer_passage": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

tidak

Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:

ds = tfds.load('huggingface:xglue/ntg')
  • Keterangan :
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/.
  • Lisensi : Tidak ada lisensi yang diketahui
  • Versi : 1.0.0
  • Perpecahan :
Membelah Contoh
'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
  • Fitur :
{
    "news_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "news_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}