Delete dga-detection.py

dga-detection.py

@@ -1,67 +0,0 @@
-import datasets
-import pandas as pd
-import os
-
-
-class MyDataset(datasets.GeneratorBasedBuilder):
-    def _info(self):
-
-        return datasets.DatasetInfo(
-            description="DESCRIPTION",
-            features=datasets.Features(
-                {"domain": datasets.Value("string"), "label": datasets.Value("string")}
-            ),
-            supervised_keys=("domain", "label"),
-            homepage="_HOMEPAGE",
-        )
-
-
-    def _split_generators(self, dl_manager: DownloadConfig):
-        # Load your local dataset file
-        csv_path = "https://huggingface.co/datasets/harpomaxx/dga-detection/raw/main/argencon.csv.gz"
-
-        return [
-            datasets.SplitGenerator(
-                name=split,
-                gen_kwargs={
-                    "filepath": csv_path,
-                    "split": split,
-                },
-            )
-            for split in ["train", "test", "validation"]
-        ]
-
-    def _generate_examples(
-            self,
-            filepath: str,
-            split: str,
-        ):
-        # Read your CSV dataset
-        dataset = pd.read_csv(filepath)
-
-        # Filter your dataset based on the 'split' argument
-        dataset = dataset[dataset["split"] == split]
-
-        # Generate examples
-        for index, row in dataset.iterrows():
-            yield index, {
-                "domain": row["domain"],
-                "label": row["label"],
-            }    
-
-    def _oldgenerate_examples(
-        self,
-        filepath: str,
-        split: str,
-    ):
-        # Read your CSV dataset
-        dataset = pd.read_csv(filepath)
-
-        # You can filter or split your dataset based on the 'split' argument if necessary
-
-        # Generate examples
-        for index, row in dataset.iterrows():
-            yield index, {
-                "domain": row["domain"],
-                "label": row["label"],
-            }