MRC

MRC/ArabicaQA.py

@@ -0,0 +1,65 @@
+from datasets import load_dataset_builder, DatasetInfo, DownloadConfig, GeneratorBasedBuilder, datasets
+
+class CustomSQuADFormatDataset(GeneratorBasedBuilder):
+    """A custom dataset similar to SQuAD but tailored for 'ArabicaQA' hosted on Hugging Face."""
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="ArabicaQA", version=VERSION, description="Custom dataset similar to SQuAD format.")
+    ]
+
+    def _info(self):
+        return DatasetInfo(
+            description="This dataset is formatted similarly to the SQuAD dataset.",
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "title": datasets.Value("string"),
+                    "context": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "answers": datasets.features.Sequence(
+                        {
+                            "text": datasets.Value("string"),
+                            "answer_start": datasets.Value("int32"),
+                        }
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/abdoelsayed/ArabicaQA",
+            citation="",
+        )
+
+    def _split_generators(self, dl_manager: DownloadConfig):
+        urls_to_download = {
+            "train": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/train.json",
+            "dev": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/val.json",
+            "test": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/test.json"
+        }
+        downloaded_files = dl_manager.download(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["test"]}),
+
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            squad_data = json.load(f)["data"]
+            for article in squad_data:
+                title = article.get("title", "")
+                for paragraph in article["paragraphs"]:
+                    context = paragraph["context"]
+                    for qa in paragraph["qas"]:
+                        id_ = qa["id"]
+                        question = qa["question"]
+                        answers = [{"text": answer["text"], "answer_start": answer["answer_start"]} for answer in qa.get("answers", [])]
+                        
+                        yield id_, {
+                            "title": title,
+                            "context": context,
+                            "question": question,
+                            "answers": answers,
+                        }