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README.md

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----
-annotations_creators:
-- no-annotation
-language_creators:
-- crowdsourced
-language:
-- en
-license:
-- cc-by-nc-3.0
-multilinguality:
-- monolingual
-size_categories:
-- 10K<n<100K
-source_datasets:
-- original
-task_categories:
-- question-answering
-task_ids:
-- closed-domain-qa
-paperswithcode_id: sciq
-pretty_name: SciQ
-dataset_info:
-  features:
-  - name: question
-    dtype: string
-  - name: distractor3
-    dtype: string
-  - name: distractor1
-    dtype: string
-  - name: distractor2
-    dtype: string
-  - name: correct_answer
-    dtype: string
-  - name: support
-    dtype: string
-  splits:
-  - name: test
-    num_bytes: 564826
-    num_examples: 1000
-  - name: train
-    num_bytes: 6556427
-    num_examples: 11679
-  - name: validation
-    num_bytes: 555019
-    num_examples: 1000
-  download_size: 2821345
-  dataset_size: 7676272
----
-
-# Dataset Card for "sciq"
-
-## Table of Contents
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [https://allenai.org/data/sciq](https://allenai.org/data/sciq)
-- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-- **Size of downloaded dataset files:** 2.69 MB
-- **Size of the generated dataset:** 7.32 MB
-- **Total amount of disk used:** 10.01 MB
-
-### Dataset Summary
-
-The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.
-
-### Supported Tasks and Leaderboards
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Languages
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Dataset Structure
-
-### Data Instances
-
-#### default
-
-- **Size of downloaded dataset files:** 2.69 MB
-- **Size of the generated dataset:** 7.32 MB
-- **Total amount of disk used:** 10.01 MB
-
-An example of 'train' looks as follows.
-```
-This example was too long and was cropped:
-
-{
-    "correct_answer": "coriolis effect",
-    "distractor1": "muon effect",
-    "distractor2": "centrifugal effect",
-    "distractor3": "tropical effect",
-    "question": "What phenomenon makes global winds blow northeast to southwest or the reverse in the northern hemisphere and northwest to southeast or the reverse in the southern hemisphere?",
-    "support": "\"Without Coriolis Effect the global winds would blow north to south or south to north. But Coriolis makes them blow northeast to..."
-}
-```
-
-### Data Fields
-
-The data fields are the same among all splits.
-
-#### default
-- `question`: a `string` feature.
-- `distractor3`: a `string` feature.
-- `distractor1`: a `string` feature.
-- `distractor2`: a `string` feature.
-- `correct_answer`: a `string` feature.
-- `support`: a `string` feature.
-
-### Data Splits
-
-| name  |train|validation|test|
-|-------|----:|---------:|---:|
-|default|11679|      1000|1000|
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-#### Who are the annotators?
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Discussion of Biases
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Other Known Limitations
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
-
-### Licensing Information
-
-The dataset is licensed under the [Creative Commons Attribution-NonCommercial 3.0 Unported License](http://creativecommons.org/licenses/by-nc/3.0/).
-
-### Citation Information
-
-```
-@inproceedings{SciQ,
-    title={Crowdsourcing Multiple Choice Science Questions},
-    author={Johannes Welbl, Nelson F. Liu, Matt Gardner},
-    year={2017},
-    journal={arXiv:1707.06209v1}
-}
-```
-
-### Contributions
-
-Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

dataset_infos.json

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-{"default": {"description": "The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.\n\n", "citation": "@inproceedings{SciQ,\n    title={Crowdsourcing Multiple Choice Science Questions},\n    author={Johannes Welbl, Nelson F. Liu, Matt Gardner},\n    year={2017},\n    journal={arXiv:1707.06209v1}\n}\n", "homepage": "https://allenai.org/data/sciq", "license": "", "features": {"question": {"dtype": "string", "id": null, "_type": "Value"}, "distractor3": {"dtype": "string", "id": null, "_type": "Value"}, "distractor1": {"dtype": "string", "id": null, "_type": "Value"}, "distractor2": {"dtype": "string", "id": null, "_type": "Value"}, "correct_answer": {"dtype": "string", "id": null, "_type": "Value"}, "support": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "sciq", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 564826, "num_examples": 1000, "dataset_name": "sciq"}, "train": {"name": "train", "num_bytes": 6556427, "num_examples": 11679, "dataset_name": "sciq"}, "validation": {"name": "validation", "num_bytes": 555019, "num_examples": 1000, "dataset_name": "sciq"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/SciQ.zip": {"num_bytes": 2821345, "checksum": "7f3312f6ac6b09970b32942d106a8c44ec0dad46a0369f17d635aff8e348a87c"}}, "download_size": 2821345, "dataset_size": 7676272, "size_in_bytes": 10497617}}

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sciq.py

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-"""TODO(sciQ): Add a description here."""
-
-
-import json
-import os
-
-import datasets
-
-
-# TODO(sciQ): BibTeX citation
-_CITATION = """\
-@inproceedings{SciQ,
-    title={Crowdsourcing Multiple Choice Science Questions},
-    author={Johannes Welbl, Nelson F. Liu, Matt Gardner},
-    year={2017},
-    journal={arXiv:1707.06209v1}
-}
-"""
-
-# TODO(sciQ):
-_DESCRIPTION = """\
-The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.
-
-"""
-_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/SciQ.zip"
-
-
-class Sciq(datasets.GeneratorBasedBuilder):
-    """TODO(sciQ): Short description of my dataset."""
-
-    # TODO(sciQ): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        # TODO(sciQ): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "question": datasets.Value("string"),
-                    "distractor3": datasets.Value("string"),
-                    "distractor1": datasets.Value("string"),
-                    "distractor2": datasets.Value("string"),
-                    "correct_answer": datasets.Value("string"),
-                    "support": datasets.Value("string"),
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://allenai.org/data/sciq",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(sciQ): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-        # download and extract URLs
-        dl_dir = dl_manager.download_and_extract(_URL)
-        data_dir = os.path.join(dl_dir, "SciQ dataset-2 3")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "train.json")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "valid.json")},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": os.path.join(data_dir, "test.json")},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(sciQ): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for id_, row in enumerate(data):
-                yield id_, row