Create dataset_script.py

dataset_script.py

@@ -0,0 +1,43 @@
+import os
+from datasets import DatasetInfo, GeneratorBasedBuilder, Split, SplitGenerator, Value, Features
+
+class CommonCorpus(GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="bytelevel", version=VERSION, description="Bytelevel corpus data"),
+    ]
+
+    def _info(self):
+        return DatasetInfo(
+            description="Common Corpus from InfoTokenizers - bytelevel config",
+            features=Features({
+                "text": Value("string"),
+            }),
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/InfoTokenizers/common-corpus",
+            citation="",
+        )
+
+    def _split_generators(self, dl_manager):
+        # Use the local extracted path to dataset files
+        data_dir = os.path.join(dl_manager.manual_dir, "bytelevel")
+
+        return [
+            SplitGenerator(
+                name=Split.TRAIN,
+                gen_kwargs={"data_dir": data_dir},
+            ),
+        ]
+
+    def _generate_examples(self, data_dir):
+        # Iterate over all .txt files inside bytelevel folder
+        file_paths = [os.path.join(data_dir, f) for f in os.listdir(data_dir) if f.endswith(".txt")]
+
+        example_id = 0
+        for file_path in file_paths:
+            with open(file_path, encoding="utf-8") as f:
+                for line in f:
+                    text = line.strip()
+                    if text:
+                        yield example_id, {"text": text}
+                        example_id += 1