Update parquet files

.gitattributes

@@ -15,3 +15,5 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
 *.csv filter=lfs diff=lfs merge=lfs -text
+default/spanish_diagnostics-train.parquet filter=lfs diff=lfs merge=lfs -text
+default/spanish_diagnostics-test.parquet filter=lfs diff=lfs merge=lfs -text

spanish_diagnostics.csv → default/spanish_diagnostics-test.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:14d674a6f896db4482c95a123115140f34e1f4767ed40700f35bb4ceaceae0cd
-size 6847038
+oid sha256:77c5691d2cb9891d7297cc0c9be169ac0463ee2b971a248481748de4fdce8360
+size 1373042

default/spanish_diagnostics-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3881e897ee4075b3c8ab7e44aaa16a00ffa1dcb8f90b9204b97a491eb8ef74e2
+size 3271739

spanish_diagnostics.py

@@ -1,41 +0,0 @@
-import csv
-import datasets
-
-_DOWNLOAD_URL = "https://huggingface.co/datasets/fvillena/spanish_diagnostics/resolve/main/spanish_diagnostics.csv"
-
-class SpanishDiagnostics(datasets.GeneratorBasedBuilder):
-    """Spanish diagnostics classification dataset."""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.ClassLabel(names = ["not_dental", "dental"] ),
-                }
-            )
-        )
-
-    def _split_generators(self, dl_manager):
-        path = dl_manager.download_and_extract(_DOWNLOAD_URL)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": path, "is_test": False}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": path, "is_test": True}),
-        ]
-
-    def _generate_examples(self, filepath, is_test, test_size = 0.3):
-        """Generate Spanish Diagnostics examples."""
-        with open(filepath, encoding="utf-8") as csv_file:
-            train_threshold = 70001
-            csv_reader = csv.reader(
-                csv_file
-            )
-            # next(csv_reader, None)  # skip the headers
-            for id_, row in enumerate(csv_reader):
-                if id_ > 0:
-                    text, label = row
-                    current_row = id_, {"text": text, "label": int(label)}
-                    if (id_ < train_threshold) & (not is_test):
-                        yield current_row
-                    if (id_ >= train_threshold) & (is_test):
-                        yield current_row