Upload mumospee_small.py with huggingface_hub

mumospee_small.py

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+import pandas as pd
+import datasets
+
+
+
+# Define the dataset to Hugging Face standard so users can access it via load_dataset
+class MumospeeSmall(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="Mumospee is a continuously growing, comprehensive, multilingual dataset across different modalities. This is the small version include no more 1000 rows.",
+            features=datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "url": datasets.Value("string"),
+                    "type": datasets.Value("string"),
+                    "duration": datasets.Value("float32"),
+                    "language": datasets.Value("string"),
+                    "transcript": datasets.Value("string"),
+                    "tag": datasets.Value("string"),
+                    "split": datasets.Value("string"),
+                    "license": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+            license="CC-BY-4.0",
+        )
+
+    def _split_generators(self, dl_manager):
+        # Specify the CSV path
+        csv_path = self.config.data_files["csv"]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"csv_path": csv_path, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"csv_path": csv_path, "split": "test"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"csv_path": csv_path, "split": "validation"},
+            ),
+        ]
+
+    
+    def _generate_examples(self, csv_path, split, language=None, tag=None):
+        """
+        Generates examples from the CSV file, applying filters based on split, language, and tag.
+        """
+
+        # Read the CSV file in chunks to handle large datasets
+        for chunk in pd.read_csv(csv_path, chunksize=10_000):
+            # Filter by split if specified
+            if split:
+                chunk = chunk[chunk["split"] == split]
+
+            # Apply language filter if provided
+            if language:
+                chunk = chunk[chunk["language"] == language]
+
+            # Apply tag filter if provided
+            if tag:
+                chunk = chunk[chunk["tag"] == tag]
+
+            # Yield examples one by one
+            for idx, record in chunk.iterrows():
+                yield idx, record.to_dict()