참고자료:
mlsum_de
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/mlsum_de')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_covid' | 5058 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 10695 |
'train' | 220748 |
'validation' | 11392 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/mlsum_es')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_covid' | 1938년 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 13366 |
'train' | 259888 |
'validation' | 9977 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_es_en_v0')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 19797 |
'train' | 79515 |
'validation' | 8835 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_ru_en_v0')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 9094 |
'train' | 36898 |
'validation' | 4100 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_tr_en_v0')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 808 |
'train' | 3193 |
'validation' | 355 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_vi_en_v0')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2167 |
'train' | 9206 |
'validation' | 1023 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_arabic_ar')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 5841 |
'train' | 20441 |
'validation' | 2919 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_chinese_zh')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 3775 |
'train' | 13211 |
'validation' | 1886년 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_czech_cs')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 1438 |
'train' | 5033 |
'validation' | 718 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_dutch_nl')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 6248 |
'train' | 21866 |
'validation' | 3123 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_english_en')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 28614 |
'train' | 99020 |
'validation' | 13823 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_french_fr')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 12731 |
'train' | 44556 |
'validation' | 6364 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_german_de')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 11669 |
'train' | 40839 |
'validation' | 5833 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_hindi_hi')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 1984년 |
'train' | 6942 |
'validation' | 991 |
- 특징 :
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"hi",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"hi",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_indonesian_id
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_indonesian_id')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 9497 |
'train' | 33237 |
'validation' | 4747 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_italian_it')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 10189 |
'train' | 35661 |
'validation' | 5093 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_japanese_ja')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2530 |
'train' | 8853 |
'validation' | 1264 |
- 특징 :
{
"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_한국어_ko
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_korean_ko')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2436 |
'train' | 8524 |
'validation' | 1216 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_portuguese_pt')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 16331 |
'train' | 57159 |
'validation' | 8165 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_russian_ru')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 10580 |
'train' | 37028 |
'validation' | 5288 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_spanish_es')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 22632 |
'train' | 79212 |
'validation' | 11316 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_thai_th')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 2950 |
'train' | 10325 |
'validation' | 1475 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_turkish_tr')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 900 |
'train' | 3148 |
'validation' | 449 |
- 특징 :
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"tr",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"tr",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
wiki_lingua_vietnamese_vi
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_lingua_vietnamese_vi')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 3917 |
'train' | 13707 |
'validation' | 1957년 |
- 특징 :
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"source_aligned": {
"languages": [
"vi",
"en"
],
"id": null,
"_type": "Translation"
},
"target_aligned": {
"languages": [
"vi",
"en"
],
"id": null,
"_type": "Translation"
},
"source": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
xsum
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/xsum')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'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 |
- 특징 :
{
"gem_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gem_parent_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"xsum_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"document": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"target": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"references": [
{
"dtype": "string",
"id": null,
"_type": "Value"
}
]
}
common_gen
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/common_gen')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 1497 |
'train' | 67389 |
'validation' | 993 |
- 특징 :
{
"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_레스토랑
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/cs_restaurants')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 842 |
'train' | 3569 |
'validation' | 781 |
- 특징 :
{
"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"
}
]
}
다트
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/dart')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'test' | 5097 |
'train' | 62659 |
'validation' | 2768 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/e2e_nlg')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 4693 |
'train' | 33525 |
'validation' | 4299 |
- 특징 :
{
"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"
}
]
}
토토
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/totto')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 500 |
'challenge_validation_sample' | 500 |
'test' | 7700 |
'train' | 121153 |
'validation' | 7700 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/web_nlg_en')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_numbers' | 500 |
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 502 |
'challenge_validation_sample' | 499 |
'test' | 1779년 |
'train' | 35426 |
'validation' | 1667년 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/web_nlg_ru')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'challenge_test_scramble' | 500 |
'challenge_train_sample' | 501 |
'challenge_validation_sample' | 500 |
'test' | 1102 |
'train' | 14630 |
'validation' | 790 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/wiki_auto_asset_turk')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'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 |
- 특징 :
{
"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
TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.
ds = tfds.load('huggingface:gem/schema_guided_dialog')
- 설명 :
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.
- 라이센스 : CC-BY-SA-4.0
- 버전 : 1.1.0
- 분할 :
| 나뉘다 | 예 |
|---|---|
'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 |
- 특징 :
{
"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"
}
]
}