Referencias:
mlsum_de
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/mlsum_de')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_covid' | 5058 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 10695 |
'train' | 220748 |
'validation' | 11392 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/mlsum_es')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_covid' | 1938 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 13366 |
'train' | 259888 |
'validation' | 9977 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 19797 |
'train' | 79515 |
'validation' | 8835 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 9094 |
'train' | 36898 |
'validation' | 4100 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 808 |
'train' | 3193 |
'validation' | 355 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 2167 |
'train' | 9206 |
'validation' | 1023 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 5841 |
'train' | 20441 |
'validation' | 2919 |
- Características :
{
"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_chino_zh
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 3775 |
'train' | 13211 |
'validation' | 1886 |
- Características :
{
"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_checo_cs
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 1438 |
'train' | 5033 |
'validation' | 718 |
- Características :
{
"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_holandés_nl
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 6248 |
'train' | 21866 |
'validation' | 3123 |
- Características :
{
"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_inglés_en
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 28614 |
'train' | 99020 |
'validation' | 13823 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 12731 |
'train' | 44556 |
'validation' | 6364 |
- Características :
{
"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_alemán_de
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 11669 |
'train' | 40839 |
'validation' | 5833 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 1984 |
'train' | 6942 |
'validation' | 991 |
- Características :
{
"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_indonesio_id
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 9497 |
'train' | 33237 |
'validation' | 4747 |
- Características :
{
"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_italiano_es
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 10189 |
'train' | 35661 |
'validation' | 5093 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 2530 |
'train' | 8853 |
'validation' | 1264 |
- Características :
{
"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_coreano_ko
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 2436 |
'train' | 8524 |
'validation' | 1216 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 16331 |
'train' | 57159 |
'validation' | 8165 |
- Características :
{
"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_ruso_ru
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 10580 |
'train' | 37028 |
'validation' | 5288 |
- Características :
{
"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_español
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 22632 |
'train' | 79212 |
'validation' | 11316 |
- Características :
{
"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_tailandés_th
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 2950 |
'train' | 10325 |
'validation' | 1475 |
- Características :
{
"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_turco_tr
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 900 |
'train' | 3148 |
'validation' | 449 |
- Características :
{
"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_vietnamita_vi
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 3917 |
'train' | 13707 |
'validation' | 1957 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/xsum')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'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 |
- Características :
{
"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"
}
]
}
gen_común
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/common_gen')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 1497 |
'train' | 67389 |
'validation' | 993 |
- Características :
{
"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_restaurantes
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/cs_restaurants')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 842 |
'train' | 3569 |
'validation' | 781 |
- Características :
{
"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"
}
]
}
dardo
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/dart')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'test' | 5097 |
'train' | 62659 |
'validation' | 2768 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/e2e_nlg')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 4693 |
'train' | 33525 |
'validation' | 4299 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/totto')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 7700 |
'train' | 121153 |
'validation' | 7700 |
- Características :
{
"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_es
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/web_nlg_en')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_numbers' | 500 |
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 502 |
'challenge_validation_sample' | 499 |
'test' | 1779 |
'train' | 35426 |
'validation' | 1667 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/web_nlg_ru')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 501 |
'challenge_validation_sample' | 500 |
'test' | 1102 |
'train' | 14630 |
'validation' | 790 |
- Características :
{
"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
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'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 |
- Características :
{
"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"
}
]
}
esquema_diálogo_guiado
Utilice el siguiente comando para cargar este conjunto de datos en TFDS:
ds = tfds.load('huggingface:gem/schema_guided_dialog')
- Descripción :
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.
- Licencia : CC-BY-SA-4.0
- Versión : 1.1.0
- Divisiones :
| Dividir | Ejemplos |
|---|---|
'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 |
- Características :
{
"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"
}
]
}