Update data_loader.py

data_loader.py

@@ -1,21 +1,23 @@
-from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split
-import datasets
+from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split, Value
 
-class SinhalaPerplexityDataset(datasets.GeneratorBasedBuilder):
+class SinhalaPerplexity(GeneratorBasedBuilder):
     def _info(self):
         return DatasetInfo(
-            features=datasets.Features({
-                "sinhala_unicode": datasets.Value("string"),
-                "sinhala_romanized": datasets.Value("string"),
-            }),
-            description="Sinhala Perplexity Test Dataset with Unicode and Romanized Sinhala sentences.",
+            description="Sinhala Unicode and Romanized sentence pairs for perplexity evaluation.",
+            features={
+                "sinhala_unicode": Value("string"),
+                "sinhala_romanized": Value("string"),
+            },
             supervised_keys=None,
         )
 
     def _split_generators(self, dl_manager):
-        data_path = dl_manager.download_and_extract("data\diverse_sentences.csv")
+        data_path = dl_manager.download("data/diverse_sentences.csv")
         return [
-            SplitGenerator(name="data", gen_kwargs={"filepath": data_path}),
+            SplitGenerator(
+                name=Split("data"),  # 👈 Your custom split name
+                gen_kwargs={"filepath": data_path},
+            )
         ]
 
     def _generate_examples(self, filepath):
@@ -24,6 +26,6 @@ class SinhalaPerplexityDataset(datasets.GeneratorBasedBuilder):
             reader = csv.DictReader(f)
             for idx, row in enumerate(reader):
                 yield idx, {
-                    "sinhala_unicode": row["sinhala_unicode"],
-                    "sinhala_romanized": row["sinhala_romanized"],
+                    "sinhala_unicode": row["unicode_sentence"],
+                    "sinhala_romanized": row["romanized_sentence"],
                 }