gem

Referencje:

mlsum_de

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:gem/mlsum_de')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_covid' 5058
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 10695
'train' 220748
'validation' 11392
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:gem/mlsum_es')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_covid' 1938
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 13366
'train' 259888
'validation' 9977
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:

ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 19797
'train' 79515
'validation' 8835
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 9094
'train' 36898
'validation' 4100
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 808
'train' 3193
'validation' 355
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 2167
'train' 9206
'validation' 1023
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 5841
'train' 20441
'validation' 2919
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 3775
'train' 13211
'validation' 1886
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 1438
'train' 5033
'validation' 718
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 6248
'train' 21866
'validation' 3123
  • Cechy : 
{
    "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_en

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 28614
'train' 99020
'validation' 13823
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 12731
'train' 44556
'validation' 6364
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 11669
'train' 40839
'validation' 5833
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 1984
'train' 6942
'validation' 991
  • Cechy : 
{
    "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_indonezyjski_id

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 9497
'train' 33237
'validation' 4747
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 10189
'train' 35661
'validation' 5093
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 2530
'train' 8853
'validation' 1264
  • Cechy : 
{
    "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_koreański_ko

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 2436
'train' 8524
'validation' 1216
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 16331
'train' 57159
'validation' 8165
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 10580
'train' 37028
'validation' 5288
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 22632
'train' 79212
'validation' 11316
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 2950
'train' 10325
'validation' 1475
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 900
'train' 3148
'validation' 449
  • Cechy : 
{
    "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_wietnamski_vi

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 3917
'train' 13707
'validation' 1957
  • Cechy : 
{
    "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"
        }
    ]
}

suma x

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/xsum')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'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
  • Cechy : 
{
    "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"
        }
    ]
}

wspólny_gen

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/common_gen')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 1497
'train' 67389
'validation' 993
  • Cechy : 
{
    "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_restauracje

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/cs_restaurants')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 842
'train' 3569
'validation' 781
  • Cechy : 
{
    "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"
        }
    ]
}

strzałka

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/dart')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'test' 5097
'train' 62659
'validation' 2768
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/e2e_nlg')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 4693
'train' 33525
'validation' 4299
  • Cechy : 
{
    "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"
        }
    ]
}

to samo

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/totto')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_scramble' 500
'challenge_train_sample' 500
'challenge_validation_sample' 500
'test' 7700
'train' 121153
'validation' 7700
  • Cechy : 
{
    "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_en

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/web_nlg_en')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_numbers' 500
'challenge_test_scramble' 500
'challenge_train_sample' 502
'challenge_validation_sample' 499
'test' 1779
'train' 35426
'validation' 1667
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/web_nlg_ru')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'challenge_test_scramble' 500
'challenge_train_sample' 501
'challenge_validation_sample' 500
'test' 1102
'train' 14630
'validation' 790
  • Cechy : 
{
    "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

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'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
  • Cechy : 
{
    "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"
        }
    ]
}

schema_guided_dialog

Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS: 

ds = tfds.load('huggingface:gem/schema_guided_dialog')
  • Opis : 
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.
  • Licencja : CC-BY-SA-4.0
  • Wersja : 1.1.0
  • Podziały :
Podział Przykłady
'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
  • Cechy : 
{
    "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"
        }
    ]
}