Delete loading script

summarization.py

@@ -1,78 +0,0 @@
-import datasets
-import os
-import json
-
-
-_CITATION = ""
-_DESCRIPTION = """
-    Scenario for single document text summarization.
-    Currently supports the following datasets:
-    1. XSum (https://arxiv.org/pdf/1808.08745.pdf)
-    2. CNN/DailyMail non-anonymized (https://arxiv.org/pdf/1704.04368.pdf)
-
-    Task prompt structure
-
-        Summarize the given document.
-        Document: {tok_1 ... tok_n}
-        Summary: {tok_1 ... tok_m}
-
-    Example from XSum dataset
-
-        Document: {Part of the Broad Road was closed to traffic on Sunday at about 18:00 GMT.
-                   The three adults and three children have been taken to Altnagelvin Hospital
-                   with non life-threatening injuries. The Fire Service, Northern Ireland Ambulance Service
-                   and police attended the crash. The Broad Road has since been reopened.}
-        Summary: {Three adults and three children have been taken to hospital following a crash involving
-                  a tractor and a campervan in Limavady, County Londonderry}
-"""
-
-class Summarization(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description="")
-            for name in ["xsum", "xsum-sampled", "cnn-dm"]
-        ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "article": datasets.Value("string"),
-                "summary": datasets.Value("string"),
-
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage="",
-            license="",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        train_json = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
-        test_json = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
-        val_json = dl_manager.download(os.path.join(self.config.name, "validation.jsonl"))
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"path": train_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"path": test_json},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"path": val_json},
-            )
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, path):
-        with open(path, encoding="utf-8") as f:
-            for key, row in enumerate(f):
-                yield key, json.loads(row)
-