Duplicate from ai4bharat/IndicQA

Co-authored-by: Sumanth Doddapaneni <sumanthd@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
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+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+*.mp3 filter=lfs diff=lfs merge=lfs -text
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+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
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.gitignore

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+.DS_Store

IndicQA.py

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+"""TODO(xquad): Add a description here."""
+
+
+import json
+
+import datasets
+
+
+_CITATION = """\
+
+"""
+
+_DESCRIPTION = """\
+
+"""
+
+_URL = "https://huggingface.co/datasets/ai4bharat/IndicQA/resolve/main/data/"
+_LANG = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]
+
+
+class IndicqaConfig(datasets.BuilderConfig):
+
+    """BuilderConfig for Indicqa"""
+
+    def __init__(self, lang, **kwargs):
+        """
+
+        Args:
+            lang: string, language for the input text
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(IndicqaConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.lang = lang
+
+
+class Xquad(datasets.GeneratorBasedBuilder):
+    """TODO(indicqa): Short description of my dataset."""
+
+    # TODO(indicqa): Set up version.
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [IndicqaConfig(name=f"indicqa.{lang}", description=_DESCRIPTION, lang=lang) for lang in _LANG]
+
+    def _info(self):
+        # TODO(indicqa): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "context": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "answers": datasets.features.Sequence(
+                        {
+                            "text": datasets.Value("string"),
+                            "answer_start": datasets.Value("int32"),
+                        }
+                    ),
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(indicqa): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        urls_to_download = {lang: _URL + f"indicqa.{lang}.json" for lang in _LANG}
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": downloaded_files[self.config.lang]},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(indicqa): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            indicqa = json.load(f)
+            id_ = 0
+            for article in indicqa["data"]:
+                for paragraph in article["paragraphs"]:
+                    context = paragraph["context"].strip()
+                    for qa in paragraph["qas"]:
+                        question = qa["question"].strip()
+                        answer_starts = [answer["answer_start"] for answer in qa["answers"]]
+                        answers = [answer["text"].strip() for answer in qa["answers"]]
+
+                        # Features currently used are "context", "question", and "answers".
+                        # Others are extracted here for the ease of future expansions.
+                        yield id_, {
+                            "context": context,
+                            "question": question,
+                            "id": qa["id"],
+                            "answers": {
+                                "answer_start": answer_starts,
+                                "text": answers,
+                            },
+                        }
+                        id_ += 1

README.md

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+---
+annotations_creators:
+- expert-generated
+language:
+- pa
+- ta
+- te
+- as
+- bn
+- hi
+- or
+- ml
+- mr
+- kn
+- gu
+language_creators:
+- found
+license:
+- cc-by-4.0
+multilinguality:
+- multilingual
+pretty_name: IndicQA
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+- closed-domain-qa
+---
+
+# Dataset Card for [Dataset Name]
+
+**Description:**
+The Indic QA dataset is designed for question answering tasks, with a focus on Indic languages. It contains questions paired with corresponding contexts and answers. The dataset aims to facilitate research and development in question answering systems for Indic languages.
+
+**Dataset Info:**
+
+**Features:**
+- **ID:** Identifier for each data instance.
+- **Context:** The passage or context providing information relevant to answering the question.
+- **Question:** The question posed by the user.
+- **Answers:** The possible answers to the question, provided as a sequence.
+  
+**Languages:**
+- **Assamese (as)**
+- **Bengali (bn)**
+- **Hindi (hi)**
+- **Kannada (kn)**
+- **Marathi (mr)**
+- **Malayalam (ml)**
+- **Punjabi (pa)**
+- **Oriya (or)**
+- **Tamil (ta)**
+- **Telugu (te)**
+
+
+Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.

data/.gitattributes

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