Create dataset.py

dataset.py

@@ -0,0 +1,44 @@
+from datasets import DatasetBuilder, DatasetInfo, SplitGenerator, Split
+
+class CustomJSONLDataset(DatasetBuilder):
+    VERSION = "1.0.0"
+
+    def _info(self) -> DatasetInfo:
+        return DatasetInfo(
+            description="Custom dataset from local JSONL files.",
+            features={"text": "string"},
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = [f"output_json_{i}.jsonl" for i in range(2, 3)]
+        
+        # The download_and_extract function can handle multiple files and will 
+        # download them in parallel if possible.
+        paths = dl_manager.download_and_extract(urls)
+
+        return [
+            SplitGenerator(
+                name=Split.TRAIN,
+                gen_kwargs={"filepaths": paths},
+            ),
+        ]
+
+    def _generate_examples(self, filepaths):
+        """Yields examples from the dataset."""
+        import json
+
+        for filepath in filepaths:
+            with open(filepath, "r", encoding="utf-8") as f:
+                for idx, line in enumerate(f):
+                    data = json.loads(line.strip())
+                    yield idx, {"text": data["text"]}
+
+# The following lines are useful for testing locally, to ensure the script works as expected.
+# They're not necessary when the script is integrated into a HuggingFace Datasets repository.
+if __name__ == "__main__":
+    from datasets import load_dataset
+
+    # This will use the custom dataset loading script.
+    dataset = load_dataset("path_to_this_script.py")
+    print(dataset["train"][0])