তথ্যসূত্র:
ডি
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/de')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 9725 |
'train' | 35458 |
'validation' | 4705 |
- বৈশিষ্ট্য :
{
"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"
}
}
fr
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/fr')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 6820 |
'train' | 21179 |
'validation' | 3095 |
- বৈশিষ্ট্য :
{
"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"
}
}
এটা
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/it')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 812 |
'train' | 3072 |
'validation' | 408 |
- বৈশিষ্ট্য :
{
"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"
}
}
সব_ভাষা
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 17357 |
'train' | 59709 |
'validation' | 8208 |
- বৈশিষ্ট্য :
{
"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"
}
}
তথ্যসূত্র:
ডি
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/de')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 9725 |
'train' | 35458 |
'validation' | 4705 |
- বৈশিষ্ট্য :
{
"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"
}
}
fr
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/fr')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 6820 |
'train' | 21179 |
'validation' | 3095 |
- বৈশিষ্ট্য :
{
"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"
}
}
এটা
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/it')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 812 |
'train' | 3072 |
'validation' | 408 |
- বৈশিষ্ট্য :
{
"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"
}
}
সব_ভাষা
TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:
ds = tfds.load('huggingface:swiss_judgment_prediction/all_languages')
- বর্ণনা :
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.
- লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
- সংস্করণ : 1.0.0
- বিভাজন :
বিভক্ত | উদাহরণ |
---|---|
'test' | 17357 |
'train' | 59709 |
'validation' | 8208 |
- বৈশিষ্ট্য :
{
"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"
}
}