Create kriyans.py

kriyans.py

@@ -0,0 +1,83 @@
+import datasets
+
+_URL = "https://colab.research.google.com/drive/1aSWUrQFWU_RJOt9NmVDRnn9ci-11dC9x#scrollTo=LOncaJUnrl8O"
+
+# Define the path to your CSV file
+csv_file_path = '/indian-name-org.csv'
+
+class YourCustomConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(YourCustomConfig, self).__init__(**kwargs)
+
+class YourCustomDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        YourCustomConfig(
+            name="your_custom_dataset",
+            version=datasets.Version("1.0.0"),
+            description="Your Custom Dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="Your custom dataset description",
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "B-PER",
+                                "I-ORG",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+         urls_to_download = {
+            "train": f"{_URL}{csv_file_path}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            current_tokens = []
+            current_labels = []
+            sentence_counter = 0
+            for row in f:
+                row = row.rstrip()
+                if row:
+                    token, label = row.split(",")
+                    current_tokens.append(token)
+                    current_labels.append(label)
+                else:
+                    if not current_tokens:
+                        continue
+                    assert len(current_tokens) == len(current_labels), "Mismatch between tokens and labels"
+                    sentence = (
+                        sentence_counter,
+                        {
+                            "id": str(sentence_counter),
+                            "tokens": current_tokens,
+                            "ner_tags": current_labels,
+                        },
+                    )
+                    sentence_counter += 1
+                    current_tokens = []
+                    current_labels = []
+                    yield sentence
+            if current_tokens:
+                yield sentence_counter, {
+                    "id": str(sentence_counter),
+                    "tokens": current_tokens,
+                    "ner_tags": current_labels,
+                }