ndupuis commited on
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Convert dataset to Parquet (#3)

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- Convert dataset to Parquet (18247da3528a271c880b46c9e2ebca49478d7c4e)
- Delete loading script (2e9c7c43bcfc10e47622556dff25dd5259b4f50e)

data/test-00000-of-00001.parquet ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:e6ef2b6e576cc66a77ddd4ac6b9bb39bd3cfb5f50baad1bcd414931e2b28d64d
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+ size 62547
qiskit_humaneval.py DELETED
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- # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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- #
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- # Licensed under the Apache License, Version 2.0 (the "License");
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- # you may not use this file except in compliance with the License.
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- # You may obtain a copy of the License at
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- #
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- # http://www.apache.org/licenses/LICENSE-2.0
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- #
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- # Unless required by applicable law or agreed to in writing, software
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- # distributed under the License is distributed on an "AS IS" BASIS,
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- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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- # See the License for the specific language governing permissions and
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- # limitations under the License.
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- """ qiskit_humaneval dataset"""
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-
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- import json
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- import datasets
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- import os
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- import requests
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _CITATION = """\
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- @misc{2406.14712,
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- 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},
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- Title = {Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models},
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- Year = {2024},
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- Eprint = {arXiv:2406.14712},
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- }
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- """
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-
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- _DESCRIPTION = """\
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- qiskit_humaneval is a dataset for evaluating LLM's at writing Qiskit code.
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- """
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-
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- _HOMEPAGE = "https://github.com/qiskit-community/qiskit-human-eval"
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-
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- _LICENSE = "apache-2.0"
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-
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- _URL = "https://raw.githubusercontent.com/qiskit-community/qiskit-human-eval/"\
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- "refs/heads/main/dataset/dataset_qiskit_test_human_eval.json"
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-
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- class QiskitHumanEval(datasets.GeneratorBasedBuilder):
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- """ qiskit_humaneval dataset
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-
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- 0.1.1: update to support Qiskit 1.4 and improve test cases
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- 0.1.0: first version of the dataset
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- """
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-
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- VERSION = datasets.Version("0.1.1")
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-
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- def _info(self):
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- features = datasets.Features(
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- {
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- 'task_id': datasets.Value('string'),
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- 'prompt': datasets.Value('string'),
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- 'canonical_solution': datasets.Value('string'),
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- 'test': datasets.Value('string'),
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- 'entry_point': datasets.Value('string'),
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- 'difficulty_scale': datasets.Value('string')
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- }
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- )
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=features,
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- homepage=_HOMEPAGE,
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- license=_LICENSE,
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- citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager: datasets.DownloadManager):
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- filepath = dl_manager.download_and_extract(_URL)
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- gen_kwargs={
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- "filepath": filepath,
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- },
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- ),
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- ]
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-
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- def _generate_examples(self, filepath):
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- with open(filepath, 'r', encoding="UTF-8") as in_json:
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- for row in json.load(in_json):
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- id_ = row['task_id']
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- yield id_, {
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- 'task_id': row['task_id'],
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- 'prompt': row['prompt'],
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- 'canonical_solution': row['canonical_solution'],
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- 'test': row['test'],
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- 'entry_point': row['entry_point'],
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- 'difficulty_scale': row['difficulty_scale']
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- }