multi_eurlex

Références:

fr

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/en')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

un

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/da')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

de

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/de')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/nl')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

sv

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/sv')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 42490
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

bg

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/bg')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 15986
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

cs

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/cs')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23187
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

heure

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/hr')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 7944
'validation' 2500
  • Caractéristiques :
{
    "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"
    }
}

PL

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/pl')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23197
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

sk

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/sk')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 22971
'validation' 5000
  • Caractéristiques :
{
    "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

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/sl')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23184
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

es

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/es')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 52785
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

en

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/fr')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

ce

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/it')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

pt

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/pt')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 52370
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

ro

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/ro')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 15921
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

et

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/et')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23126
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

Fi

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/fi')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 42497
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

heu

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/hu')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 22664
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

ça

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/lt')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23188
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

LV

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/lv')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 23208
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

el

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/el')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

mt

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/mt')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 17521
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}

toutes les langues

Utilisez la commande suivante pour charger cet ensemble de données dans TFDS :

ds = tfds.load('huggingface:multi_eurlex/all_languages')
  • Descriptif :
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).
  • Licence : Aucune licence connue
  • Version : 1.0.0
  • Fractionnements :
Diviser Exemples
'test' 5000
'train' 55000
'validation' 5000
  • Caractéristiques :
{
    "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"
    }
}