টাইডিকা

তথ্যসূত্র:

• কোড
• আলিঙ্গন মুখ

প্রাথমিক_টাস্ক

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:tydiqa/primary_task')

• বর্ণনা :

TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs.
The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language
expresses -- such that we expect models performing well on this set to generalize across a large number of the languages
in the world. It contains language phenomena that would not be found in English-only corpora. To provide a realistic
information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but
don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language without
the use of translation (unlike MLQA and XQuAD).

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.0.0
• বিভাজন :

বিভক্ত	উদাহরণ
'train'	166916
'validation'	18670

• বৈশিষ্ট্য :

{
    "passage_answer_candidates": {
        "feature": {
            "plaintext_start_byte": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "plaintext_end_byte": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "question_text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "document_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "language": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "annotations": {
        "feature": {
            "passage_answer_candidate_index": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "minimal_answers_start_byte": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "minimal_answers_end_byte": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            },
            "yes_no_answer": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "document_plaintext": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "document_url": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

সেকেন্ডারি_টাস্ক

TFDS এ এই ডেটাসেট লোড করতে নিম্নলিখিত কমান্ডটি ব্যবহার করুন:

ds = tfds.load('huggingface:tydiqa/secondary_task')

• বর্ণনা :

TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs.
The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language
expresses -- such that we expect models performing well on this set to generalize across a large number of the languages
in the world. It contains language phenomena that would not be found in English-only corpora. To provide a realistic
information-seeking task and avoid priming effects, questions are written by people who want to know the answer, but
don’t know the answer yet, (unlike SQuAD and its descendents) and the data is collected directly in each language without
the use of translation (unlike MLQA and XQuAD).

• লাইসেন্স : কোনো পরিচিত লাইসেন্স নেই
• সংস্করণ : 1.0.0
• বিভাজন :

বিভক্ত	উদাহরণ
'train'	49881
'validation'	5077

• বৈশিষ্ট্য :

{
    "id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "context": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "answers": {
        "feature": {
            "text": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "answer_start": {
                "dtype": "int32",
                "id": null,
                "_type": "Value"
            }
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    }
}