Convert dataset to new format with data files and YAML metadata

- Remove deprecated Python script
- Add data/train.txt and data/test.txt
- Update README.md with dataset card and YAML configuration

README.md

@@ -1,3 +1,44 @@
 ---
 license: apache-2.0
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    path: data/train.txt
+  - name: test
+    path: data/test.txt
 ---
+
+# UTS2017_Bank Dataset
+
+This dataset contains Vietnamese banking-related text samples for NLP tasks.
+
+## Dataset Structure
+
+The dataset contains text samples split into:
+- **train**: Training set with banking-related Vietnamese text
+- **test**: Test set with banking-related Vietnamese text
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("undertheseanlp/UTS2017_Bank")
+```
+
+## Features
+
+- `text`: Vietnamese text string related to banking and finance
+
+## Citation
+
+```bibtex
+@dataset{uts2017_bank,
+  title={UTS2017_Bank},
+  author={UnderTheSea NLP},
+  year={2017}
+}
+```

UTS2017_Bank.py

@@ -1,59 +0,0 @@
-import datasets
-
-_DESCRIPTION = """\
-UTS2017_Bank
-"""
-
-_CITATION = """\
-"""
-
-
-class UTS2017Bank(datasets.GeneratorBasedBuilder):
-    """UTS Word Tokenize datasets"""
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=None,
-            citation=_CITATION
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-
-        # Sample texts for train and test
-        train_texts = [
-            "Ngân hàng Nhà nước Việt Nam",
-            "Tài khoản tiết kiệm lãi suất cao"
-        ]
-
-        test_texts = [
-            "Chuyển khoản nhanh 24/7",
-            "Vay tín chấp không thế chấp"
-        ]
-
-        splits = [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"texts": train_texts}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"texts": test_texts}
-            )
-        ]
-        return splits
-
-    def _generate_examples(self, texts):
-        for guid, text in enumerate(texts):
-            item = {
-                "text": text
-            }
-            yield guid, item

data/test.txt

@@ -0,0 +1,2 @@
+Chuyển khoản nhanh 24/7
+Vay tín chấp không thế chấp

data/train.txt

@@ -0,0 +1,2 @@
+Ngân hàng Nhà nước Việt Nam
+Tài khoản tiết kiệm lãi suất cao