gemme

Les références:

mlsum_de

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/mlsum_de')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_covid' 5058
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 10695
'train' 220748
'validation' 11392
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

mlsum_es

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/mlsum_es')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_covid' 1938
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 13366
'train' 259888
'validation' 9977
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "topic": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_es_en_v0

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 19797
'train' 79515
'validation' 8835
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_ru_en_v0

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 9094
'train' 36898
'validation' 4100
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_tr_en_v0

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 808
'train' 3193
'validation' 355
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_vi_en_v0

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 2167
'train' 9206
'validation' 1023
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_arabic_ar

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 5841
'train' 20441
'validation' 2919
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "ar",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "ar",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_chinese_zh

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 3775
'train' 13211
'validation' 1886
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "zh",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "zh",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_czech_cs

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 1438
'train' 5033
'validation' 718
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "cs",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_dutch_nl

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 6248
'train' 21866
'validation' 3123
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "nl",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "nl",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_english_fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 28614
'train' 99020
'validation' 13823
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "en",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "en",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_french_fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 12731
'train' 44556
'validation' 6364
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "fr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "fr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_german_de

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 11669
'train' 40839
'validation' 5833
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "de",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_hindi_hi

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 1984
'train' 6942
'validation' 991
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "hi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "hi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_indonesian_id

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 9497
'train' 33237
'validation' 4747
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "id",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "id",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_italian_it

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 10189
'train' 35661
'validation' 5093
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "it",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "it",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_japanese_ja

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 2530
'train' 8853
'validation' 1264
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "ja",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "ja",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_korean_ko

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 2436
'train' 8524
'validation' 1216
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "ko",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "ko",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_portuguese_pt

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 16331
'train' 57159
'validation' 8165
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "pt",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "pt",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_russian_ru

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 10580
'train' 37028
'validation' 5288
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "ru",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "ru",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_spanish_es

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 22632
'train' 79212
'validation' 11316
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "es",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "es",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_thai_th

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 2950
'train' 10325
'validation' 1475
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "th",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "th",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_turkish_tr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 900
'train' 3148
'validation' 449
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "tr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "tr",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

wiki_lingua_vietnamese_vi

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 3917
'train' 13707
'validation' 1957
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source_aligned": {
        "languages": [
            "vi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "target_aligned": {
        "languages": [
            "vi",
            "en"
        ],
        "id": null,
        "_type": "Translation"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

xsum

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/xsum')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_backtranslation' 500
'challenge_test_bfp_02' 500
'challenge_test_bfp_05' 500
'challenge_test_covid' 401
'challenge_test_nopunc' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 1166
'train' 23206
'validation' 1117
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "xsum_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "document": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

common_gen

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/common_gen')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 1497
'train' 67389
'validation' 993
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "concept_set_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "concepts": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

cs_restaurants

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/cs_restaurants')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 842
'train' 3569
'validation' 781
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "dialog_act": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "dialog_act_delexicalized": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target_delexicalized": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

dard

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/dart')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'test' 5097
'train' 62659
'validation' 2768
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "dart_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "tripleset": [
        [
            {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        ]
    ],
    "subtree_was_extended": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    },
    "target_sources": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

e2e_nlg

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/e2e_nlg')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 4693
'train' 33525
'validation' 4299
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "meaning_representation": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

toto

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/totto')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 7700
'train' 121153
'validation' 7700
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "totto_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "table_page_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "table_webpage_url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "table_section_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "table_section_text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "table": [
        [
            {
                "column_span": {
                    "dtype": "int32",
                    "id": null,
                    "_type": "Value"
                },
                "is_header": {
                    "dtype": "bool",
                    "id": null,
                    "_type": "Value"
                },
                "row_span": {
                    "dtype": "int32",
                    "id": null,
                    "_type": "Value"
                },
                "value": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                }
            }
        ]
    ],
    "highlighted_cells": [
        [
            {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        ]
    ],
    "example_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence_annotations": [
        {
            "original_sentence": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sentence_after_deletion": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "sentence_after_ambiguity": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "final_sentence": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        }
    ],
    "overlap_subset": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

web_nlg_fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/web_nlg_en')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_numbers' 500
'challenge_test_scramble' 500
'challenge_train_sample' 502
'challenge_validation_sample' 499
'test' 1779
'train' 35426
'validation' 1667
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "input": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "webnlg_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

web_nlg_ru

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/web_nlg_ru')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_scramble' 500
'challenge_train_sample' 501
'challenge_validation_sample' 500
'test' 1102
'train' 14630
'validation' 790
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "input": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "webnlg_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

wiki_auto_asset_turk

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_asset_backtranslation' 359
'challenge_test_asset_bfp02' 359
'challenge_test_asset_bfp05' 359
'challenge_test_asset_nopunc' 359
'challenge_test_turk_backtranslation' 359
'challenge_test_turk_bfp02' 359
'challenge_test_turk_bfp05' 359
'challenge_test_turk_nopunc' 359
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test_asset' 359
'test_turk' 359
'train' 483801
'validation' 20000
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "source": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}

schéma_guide_dialog

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:gem/schema_guided_dialog')
  • Description :
GEM is a benchmark environment for Natural Language Generation with a focus on its Evaluation,
both through human annotations and automated Metrics.

GEM aims to:
- measure NLG progress across 13 datasets spanning many NLG tasks and languages.
- provide an in-depth analysis of data and models presented via data statements and challenge sets.
- develop standards for evaluation of generated text using both automated and human metrics.

It is our goal to regularly update GEM and to encourage toward more inclusive practices in dataset development
by extending existing data or developing datasets for additional languages.
  • Licence : CC-BY-SA-4.0
  • Version : 1.1.0
  • Divisions :
Diviser Exemples
'challenge_test_backtranslation' 500
'challenge_test_bfp02' 500
'challenge_test_bfp05' 500
'challenge_test_nopunc' 500
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 10000
'train' 164982
'validation' 10000
  • Caractéristiques :
{
    "gem_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gem_parent_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "dialog_acts": [
        {
            "act": {
                "num_classes": 18,
                "names": [
                    "AFFIRM",
                    "AFFIRM_INTENT",
                    "CONFIRM",
                    "GOODBYE",
                    "INFORM",
                    "INFORM_COUNT",
                    "INFORM_INTENT",
                    "NEGATE",
                    "NEGATE_INTENT",
                    "NOTIFY_FAILURE",
                    "NOTIFY_SUCCESS",
                    "OFFER",
                    "OFFER_INTENT",
                    "REQUEST",
                    "REQUEST_ALTS",
                    "REQ_MORE",
                    "SELECT",
                    "THANK_YOU"
                ],
                "id": null,
                "_type": "ClassLabel"
            },
            "slot": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "values": [
                {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                }
            ]
        }
    ],
    "context": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ],
    "dialog_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "service": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "turn_id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "prompt": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "references": [
        {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        }
    ]
}