مراجع:
أون
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/en')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
دا
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/da')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
دي
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/de')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
nl
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/nl')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
القديس
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/sv')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 42490 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
بغ
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/bg')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 15986 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
خدمات العملاء
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/cs')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23187 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ساعة
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/hr')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 7944 |
'validation' | 2500 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
رر
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/pl')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23197 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
كورونا
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/sk')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 22971 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
sl
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/sl')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23184 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
وفاق
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/es')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 52785 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
الاب
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/fr')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
هو - هي
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/it')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
نقطة
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/pt')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 52370 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ريال عماني
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/ro')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 15921 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
وآخرون
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/et')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23126 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
فاي
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/fi')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 42497 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
هو
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/hu')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 22664 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
لتر
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/lt')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23188 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
المستوى
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/lv')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 23208 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ش
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/el')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
جبل
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/mt')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 17521 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
all_languages
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:multi_eurlex/all_languages')
- وصف :
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given the text, predict multiple labels).
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 1.0.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- سمات :
{
"celex_id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"languages": [
"en",
"da",
"de",
"nl",
"sv",
"bg",
"cs",
"hr",
"pl",
"sk",
"sl",
"es",
"fr",
"it",
"pt",
"ro",
"et",
"fi",
"hu",
"lt",
"lv",
"el",
"mt"
],
"id": null,
"_type": "Translation"
},
"labels": {
"feature": {
"num_classes": 21,
"names": [
"100149",
"100160",
"100148",
"100147",
"100152",
"100143",
"100156",
"100158",
"100154",
"100153",
"100142",
"100145",
"100150",
"100162",
"100159",
"100144",
"100151",
"100157",
"100161",
"100146",
"100155"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}