सन्दर्भ:
एन
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/en')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
दा
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/da')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
डे
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/de')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/nl')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
एसवी
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/sv')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 42490 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
बीजी
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/bg')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 15986 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
सी
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/cs')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23187 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
मानव संसाधन
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/hr')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 7944 |
'validation' | 2500 |
- विशेषताएँ :
{
"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"
}
}
पी एल
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/pl')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23197 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
एसके
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/sk')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 22971 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
क्र
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/sl')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23184 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
तों
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/es')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 52785 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
फादर
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/fr')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
यह
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/it')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
पीटी
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/pt')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 52370 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
आरओ
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/ro')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 15921 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
एट
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/et')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23126 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
फाई
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/fi')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 42497 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
हू
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/hu')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 22664 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
लेफ्टिनेंट
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/lt')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23188 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
एल.वी
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/lv')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 23208 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
एल
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/el')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
मीट्रिक टन
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/mt')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 17521 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}
सारी भाषाएँ
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:multi_eurlex/all_languages')
- विवरण :
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).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 1.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'test' | 5000 |
'train' | 55000 |
'validation' | 5000 |
- विशेषताएँ :
{
"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"
}
}