removed loading script and added frontmatter

README.md

@@ -1,14 +1,30 @@
 ---
 language:
-- en
+  - en
 tags:
-- fine-tuning
-- shakespeare
+  - fine-tuning
+  - shakespeare
 pretty_name: SandMec
 size_categories:
-- n<10K
+  - n<10K
 task-categories:
-- text-generation
+  - text-generation
+
+configs:
+  - default
+
+dataset_info:
+    features:
+      - name: id
+        dtype: string
+      - name: translated_dialog
+        dtype: string
+      - name: og_response
+        dtype: string
+    config_name: default
+    splits:
+      - name: train
+      - name: test
 ---
 
 # Dataset Card for `Shakespearean and Modern English Conversational Dataset`

shakespearean-and-modern-english-conversational-dataset.py

@@ -1,73 +0,0 @@
-import datasets
-from datasets import DatasetInfo
-from datasets.download.download_manager import DownloadManager
-
-import pandas as pd
-
-_DESCRIPTION = """\
-Shakespearean and Modern English Conversational Dataset (SandMec) is a\
-converational dataset containing modern-english translated dialogs from\
-Shakespeare's works and the actual response to those dialogs as\
-present in the actual works.
-"""
-
-_URL = "https://github.com/Roudranil/shakespearean-chatbot/tree/main/processed-data/"
-_URLS = {"train": _URL + "train-v1.csv", "test": _URL + "test-v1.csv"}
-
-
-class SandMecConfig(datasets.BuilderConfig):
-    """BuilderConfig for SandMec"""
-
-    def __init__(self, **kwargs):
-        super(SandMecConfig, self).__init__(**kwargs)
-
-
-class SandMec(datasets.GeneratorBasedBuilder):
-    """SandMec: The Shakespearean and Modern English Conversational Dataset (v1)"""
-
-    VERSION = datasets.Version("1.0.0", "")
-    DEFAULT_CONFIG_NAME = "default"
-    BUILDER_CONFIGS = [
-        SandMecConfig(
-            name="plain_text",
-            version=datasets.Version("1.0.0.", ""),
-            description="Plain text",
-        ),
-    ]
-
-    def _info(self) -> DatasetInfo:
-        return DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "translated_dialog": datasets.Value("string"),
-                    "og_response": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-        )
-
-    def _split_generators(self, dl_manager: DownloadManager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": downloaded_files["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": downloaded_files["test"]},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        dataset = pd.read_csv(filepath)
-        for _, row in dataset.iterrows():
-            id_ = row["id"]
-            translated_dialog = row["translated_dialog"]
-            response = row["og_response"]
-            yield id_, {
-                "translated_dialog": translated_dialog,
-                "response": response,
-            }