Referencje:
de
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/de')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 9725 |
'train' | 35458 |
'validation' | 4705 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ks
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/fr')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 6820 |
'train' | 21179 |
'validation' | 3095 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
To
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/it')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 812 |
'train' | 3072 |
'validation' | 408 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
wszystkie_języki
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 17357 |
'train' | 59709 |
'validation' | 8208 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
Referencje:
de
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/de')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 9725 |
'train' | 35458 |
'validation' | 4705 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
ks
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/fr')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 6820 |
'train' | 21179 |
'validation' | 3095 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
To
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/it')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 812 |
'train' | 3072 |
'validation' | 408 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
wszystkie_języki
Użyj następującego polecenia, aby załadować ten zestaw danych do TFDS:
ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')
- Opis :
Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with
the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task.
We also provide additional metadata, i.e., the publication year, the legal area and the canton of origin per case,
to promote robustness and fairness studies on the critical area of legal NLP.
- Licencja : Brak znanej licencji
- Wersja : 1.0.0
- Podziały :
| Podział | Przykłady |
|---|---|
'test' | 17357 |
'train' | 59709 |
'validation' | 8208 |
- Cechy :
{
"id": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"year": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"num_classes": 2,
"names": [
"dismissal",
"approval"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"language": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"region": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"canton": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"legal area": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}