Delete loading script

qiskit_humaneval.py

@@ -1,92 +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.
-""" qiskit_humaneval dataset"""
-
-import json
-import datasets
-import os
-import requests
-logger = datasets.logging.get_logger(__name__)
-
-
-_CITATION = """\
-@misc{2406.14712,
-Author = {Sanjay Vishwakarma and Francis Harkins and Siddharth Golecha and Vishal Sharathchandra Bajpe and Nicolas Dupuis and Luca Buratti and David Kremer and Ismael Faro and Ruchir Puri and Juan Cruz-Benito},
-Title = {Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models},
-Year = {2024},
-Eprint = {arXiv:2406.14712},
-}
-"""
-
-_DESCRIPTION = """\
-qiskit_humaneval is a dataset for evaluating LLM's at writing Qiskit code.
-"""
-
-_HOMEPAGE = "https://github.com/qiskit-community/qiskit-human-eval"
-
-_LICENSE = "apache-2.0"
-
-_URL = "https://raw.githubusercontent.com/qiskit-community/qiskit-human-eval/"\
-        "refs/heads/main/dataset/dataset_qiskit_test_human_eval.json"
-
-class QiskitHumanEval(datasets.GeneratorBasedBuilder):
-    """ qiskit_humaneval dataset
-
-    0.1.0: first version of the dataset
-    """
-
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                'task_id': datasets.Value('string'),
-                'prompt': datasets.Value('string'),
-                'canonical_solution': datasets.Value('string'),
-                'test': datasets.Value('string'),
-                'entry_point': datasets.Value('string'),
-                'difficulty_scale': datasets.Value('string')
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        filepath = dl_manager.download_and_extract(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": filepath,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, 'r', encoding="UTF-8") as in_json:
-            for row in json.load(in_json):
-                id_ = row['task_id']
-                yield id_, {
-                    'task_id': row['task_id'],
-                    'prompt': row['prompt'],
-                    'canonical_solution': row['canonical_solution'],
-                    'test': row['test'],
-                    'entry_point': row['entry_point'],
-                    'difficulty_scale': row['difficulty_scale']
-                }