upload summarization data

.gitattributes

@@ -25,3 +25,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+train_data.json filter=lfs diff=lfs merge=lfs -text
+validation_data.json filter=lfs diff=lfs merge=lfs -text

book-summarization.py

@@ -0,0 +1,74 @@
+
+import json
+import pandas as pd
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+Korean Book Summarization Data
+"""
+
+_URL = "https://huggingface.co/datasets/LeverageX/book-summarization/resolve/main/"
+_URLS = {
+    "train_data": _URL + "train_data.json",
+    "validation_data": _URL + "validation_data.json",
+}
+
+class KoreanNewspaper(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="Aihub Book Summarization",
+            version=datasets.Version("1.0.0", ""),
+            description="Korean Summarization Data",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "name": datasets.Value("string"),
+                    "publisher": datasets.Value("string"),
+                    "passage": datasets.Value("string"),
+                    "summary": datasets.Value("string"),
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage="https://aihub.or.kr/aidata/30713",
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train_data"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation_data"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        key = 0
+        with open(filepath, encoding="utf-8") as f :
+            data = json.load(f)
+
+        for info in data :
+            doc_id = info['id']  
+            doc_name = info['name']
+            publisher = info['publisher']
+            passage = info['passage']
+            summary = info['summary']
+
+            yield key, {
+                "id" : doc_id,
+                "name" : doc_name,
+                "publisher" : publisher,
+                "passage" : passage,
+                "summary" : summary,
+            }
+            key += 1

train_data.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b52e380c110d3d9cf3c0d9336bee3c876d7d19e47ff7a1821c88ed89e2160ccb
+size 456828010

validation_data.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca1a64ca2593b9d8ec4a0cd950737a645ac3d954ba8f59097cc6e92c82c09901
+size 56153159