Delete adaptable_5k.py

adaptable_5k.py

@@ -1,100 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""This loads the AdapTable-5k dataset."""
-
-import json
-import os
-import pandas as pd
-
-import datasets
-
-
-# TODO: Add BibTeX citation
-_CITATION = """\
-@InProceedings{huggingface:dataset,
-title = {TODO: UPDATE TITLE HERE},
-author={TODO: BUT AUTHORS HERE},
-year={2020}
-}
-"""
-
-# TODO: Update description
-_DESCRIPTION = """\
-The AdapTable dataset consists of tables that naturally occur on the web, that are formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
-"""
-
-# TODO: Add a link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-_LICENSE = "Apache 2.0"
-
-_URL = "https://huggingface.co/datasets/MicPie/adaptable_5k/resolve/main/data/adaptable_5k.jsonl"
-
-logger = datasets.logging.get_logger(__name__)
-
-
-class AdapTable5k(datasets.GeneratorBasedBuilder):
-    # TODO: Update docs:
-    """
-    The AdapTable dataset consists of tables that naturally occur on the web, that are formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card.
-    """
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "task": datasets.Value("string"),
-                "input": datasets.Value("string"),
-                "output": datasets.Value("string"),
-                "options": datasets.Sequence([datasets.Value("string")]),
-                "pageTitle": datasets.Value("string"),
-                "outputColName": datasets.Value("string"),
-                "url": datasets.Value("string"),
-                "wdcFile": datasets.Value("string")
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download_and_extract(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": data_dir},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as f:
-            for i, row in enumerate(f):
-                data = json.loads(row)
-                key = f"{data['task']}_{i}"
-                yield key, {
-                    "task": data["task"],
-                    "input": data["input"],
-                    "output": data["output"],
-                    "options": data["options"],
-                    "pageTitle": data["pageTitle"],
-                    "outputColName": data["outputColName"],
-                    "url": data["url"],
-                    "wdcFile": data["wdcFile"],
-                }