Delete dataset.py

dataset.py

@@ -1,44 +0,0 @@
-import csv
-from datasets import DatasetInfo, Features, Value, SplitGenerator, Split, GeneratorBasedBuilder
-
-_CITATION = ""
-_DESCRIPTION = "Medical translation pairs with semantic glosses and UMLS CUIs."
-
-class MedicalTSV(GeneratorBasedBuilder):
-    VERSION = "1.0.0"
-
-    def _info(self):
-        return DatasetInfo(
-            description=_DESCRIPTION,
-            features=Features({
-                "sentence_id": Value("string"),
-                "src_lang": Value("string"),
-                "tgt_lang": Value("string"),
-                "gender_variant": Value("string"),
-                "source_text": Value("string"),
-                "target_text": Value("string"),
-                "semantic_gloss": Value("string"),
-                "CUI_semantic_gloss": Value("string"),
-            }),
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # If you later add dev/test, replicate with different files or config.
-        train_path = dl_manager.manual_dir / "train.tsv"
-        return [SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": train_path})]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, "r", encoding="utf-8") as f:
-            reader = csv.DictReader(f, delimiter="\t")
-            for i, row in enumerate(reader):
-                yield i, {
-                    "sentence_id": row.get("sentence_id", ""),
-                    "src_lang": row.get("src_lang", ""),
-                    "tgt_lang": row.get("tgt_lang", ""),
-                    "gender_variant": row.get("gender_variant", ""),
-                    "source_text": row.get("source_text", ""),
-                    "target_text": row.get("target_text", ""),
-                    "semantic_gloss": row.get("semantic_gloss", ""),
-                    "CUI_semantic_gloss": row.get("CUI_semantic_gloss", ""),
-                }