all data

ArabicaQA.py

@@ -1,66 +0,0 @@
-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,
-                        }

arabicaqa.py

@@ -1,85 +0,0 @@
-import csv
-import json
-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, including CSV data."
-        )
-    ]
-
-    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"),
-                        }
-                    ),
-                    # Additional fields from the CSV can be added here if needed
-                }
-            ),
-            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",
-            "csv": "https://huggingface.co/datasets/abdoelsayed/ArabicaQA/raw/main/MRC/all_data_meta.csv"
-        }
-        downloaded_files = dl_manager.download(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"json_filepath": downloaded_files["train"], "csv_filepath": downloaded_files["csv"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"json_filepath": downloaded_files["dev"], "csv_filepath": downloaded_files["csv"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"json_filepath": downloaded_files["test"], "csv_filepath": downloaded_files["csv"]}),
-        ]
-
-    def _generate_examples(self, json_filepath, csv_filepath):
-        # Read the CSV file and store it in memory
-        csv_data = {}
-        with open(csv_filepath, encoding="utf-8") as csv_file:
-            csv_reader = csv.DictReader(csv_file)
-            for row in csv_reader:
-                csv_data[row['question_id']] = row
-
-        # Read the JSON file and yield examples
-        with open(json_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", [])]
-
-                        # Combine data from the CSV if present
-                        additional_csv_data = csv_data.get(id_, {})
-                        # Include additional fields from the CSV in the example if necessary
-                        example = {
-                            "title": title,
-                            "context": context,
-                            "question": question,
-                            "answers": answers,
-                            # Add additional fields from the CSV here
-                        }
-                        yield id_, example