Delete fever-span-annotated.py

fever-span-annotated.py

@@ -1,60 +0,0 @@
-import gzip
-import pandas as pd
-import datasets
-from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split
-import csv
-from itertools import islice
-
-class FeverDataset(GeneratorBasedBuilder):
-    VERSION = "1.0.0"
-    _URLS = [
-        "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000000.tsv.gz",
-        "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000001.tsv.gz",
-        "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000002.tsv.gz",
-        "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000003.tsv.gz",
-        "https://huggingface.co/datasets/jinaai/fever-span-annotated/resolve/main/data/fever-pairs_shard_000004.tsv.gz",
-    ]
-
-    def _info(self):
-        return DatasetInfo(
-            description="FEVER Dataset with span annotations.",
-            features=datasets.Features({
-                "query": datasets.Value("string"),
-                "document": datasets.Value("string"),
-                "spans": datasets.Value("string"),
-            }),
-            supervised_keys=None,
-            homepage="https://huggingface.co/datasets/jinaai/fever-span-annotated",
-            license="CC BY 4.0",
-            splits={
-                "test": {"num_bytes": 0},   # Placeholder, will be updated later
-            },
-            dataset_size=0,
-            download_size=0
-        )
-
-    def _split_generators(self, dl_manager):
-        urls_to_download = self._URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-        
-        return [
-            SplitGenerator(
-                name=Split.TEST,
-                gen_kwargs={"file_paths": downloaded_files},
-            ),
-        ]
-
-    def _generate_examples(self, file_paths):
-        for file_path in file_paths:
-            with gzip.open(file_path, 'rt') as file:
-                reader = csv.reader(
-                    file,
-                    dialect='excel-tab' if self._dialect == 'tsv' else 'excel',
-                )
-                for row in islice(reader, self._current_index, None, self._stride):
-                    if len(row) >= 3:
-                        yield row[0], {
-                            "query": row[0],
-                            "document": row[1],
-                            "spans": row[2],
-                        }