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Browse files- README.md +31 -0
- loco_queries.py +104 -0
- qmsum_test.jsonl +0 -0
README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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# LoCoV1 Queries
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The queries for the LoCoV1 dataset from the paper, "Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT"
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## How to Use
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To load the dataset, use the following command:
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```
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from datasets import load_dataset
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dataset = load_dataset("hazyresearch/LoCoV1-Queries")
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```
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To load a specific subset, such as SummScreenFD, use the following command:
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```
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from datasets import load_dataset
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dataset = load_dataset("hazyresearch/LoCoV1-Queries")
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def filter_condition(example):
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return example['dataset'] == 'summ_screen_fd'
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filtered_dataset = dataset.filter(filter_condition)
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```
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The datasets available are:
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```
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{'summ_screen_fd', 'gov_report', 'qmsum', 'qasper_title', 'qasper_abstract', '2wikimqa', 'multifieldqa',
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'passage_retrieval', 'courtlistener_HTML', 'courtlistener_Plain_Text', 'legal_case_reports', 'stackoverflow'}
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```
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For documents, go to [hazyresearch/LoCoV1-Documents](https://huggingface.co/datasets/hazyresearch/LoCoV1-Documents).
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loco_queries.py
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import csv
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import json
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import os
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import datasets
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import pandas as pd
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import zipfile
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_CITATION = """
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"""
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_DESCRIPTION = """\
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LoCoV1 Dataset - Queries
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"""
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_HOMEPAGE = "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries"
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_LICENSE = ""
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_URL = {
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"summ_screen_fd": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/summ_screen_fd",
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"gov_report": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/gov_report",
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"qmsum": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/qmsum",
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"qasper_title": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/qasper_title",
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"qasper_abstract": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/qasper_abstract",
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"multifieldqa": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/multifieldqa",
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"2wikimqa": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/2wikimqa",
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"passage_retrieval": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/passage_retrieval",
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"courtlistener_HTML": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/courtlistener_HTML",
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"courtlistener_Plain_Text": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/courtlistener_Plain_Text",
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"legal_case_reports": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/legal_case_reports",
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"stackoverflow": "https://huggingface.co/datasets/hazyresearch/LoCoV1-Queries/raw/main/queries/stackoverflow",
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}
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class NewDataset(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.1.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="summ_screen_fd", version=VERSION, description=""),
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datasets.BuilderConfig(name="gov_report", version=VERSION, description=""),
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datasets.BuilderConfig(name="qmsum", version=VERSION, description=""),
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datasets.BuilderConfig(name="qasper_title", version=VERSION, description=""),
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datasets.BuilderConfig(name="qasper_abstract", version=VERSION, description=""),
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datasets.BuilderConfig(name="multifieldqa", version=VERSION, description=""),
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datasets.BuilderConfig(name="2wikimqa", version=VERSION, description=""),
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datasets.BuilderConfig(name="passage_retrieval", version=VERSION, description=""),
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datasets.BuilderConfig(name="courtlistener_HTML", version=VERSION, description=""),
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datasets.BuilderConfig(name="courtlistener_Plain_Text", version=VERSION, description=""),
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datasets.BuilderConfig(name="legal_case_reports", version=VERSION, description=""),
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datasets.BuilderConfig(name="stackoverflow", version=VERSION, description=""),
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]
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DEFAULT_CONFIG_NAME = "summ_screen_fd" # It's not mandatory to have a default configuration. Just use one if it make sense.
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def _info(self):
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features = datasets.Features(
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{
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"qid": datasets.Value("string"),
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"dataset": datasets.Value("string"),
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"query": datasets.Value("string"),
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"answer_pids": 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, # Here we define them above because they are different between the two configurations
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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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def _split_generators(self, dl_manager):
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_URLS = {
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"test": _URL[self.config.name] + "_test.jsonl",
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}
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downloaded_files = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(name="test", gen_kwargs={"filepath": downloaded_files["test"]}),
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]
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# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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def _generate_examples(self, filepath):
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with open(filepath, encoding="utf-8") as f:
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for key, row in enumerate(f):
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data = json.loads(row)
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yield key, {
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"qid": data["qid"],
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"dataset": data["dataset"],
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"query": data["query"],
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"answer_pids": data["answer_pids"]
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}
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qmsum_test.jsonl
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