added all with msmarco

.gitattributes

@@ -56,3 +56,29 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+cqadupstack-android.jsonl.gz filter=lfs diff=lfs merge=lfs -text
+cqadupstack-gaming.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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+scidocs.jsonl.gz filter=lfs diff=lfs merge=lfs -text
+arguana.jsonl.gz filter=lfs diff=lfs merge=lfs -text
+climate-fever.jsonl.gz filter=lfs diff=lfs merge=lfs -text
+trec-covid.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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arguana.jsonl.gz

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beir-corpus.py

@@ -0,0 +1,121 @@
+# coding=utf-8
+# 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.
+
+# Lint as: python3
+
+import json
+
+import datasets
+
+_CITATION = '''
+@inproceedings{
+    thakur2021beir,
+    title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
+    author={Nandan Thakur and Nils Reimers and Andreas R{\"u}ckl{\'e} and Abhishek Srivastava and Iryna Gurevych},
+    booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
+    year={2021},
+    url={https://openreview.net/forum?id=wCu6T5xFjeJ}
+}
+'''
+
+all_data = [
+    'arguana',
+    'climate-fever',
+    'cqadupstack-android',
+    'cqadupstack-english',
+    'cqadupstack-gaming',
+    'cqadupstack-gis',
+    'cqadupstack-mathematica',
+    'cqadupstack-physics',
+    'cqadupstack-programmers',
+    'cqadupstack-stats',
+    'cqadupstack-tex',
+    'cqadupstack-unix',
+    'cqadupstack-webmasters',
+    'cqadupstack-wordpress',
+    'dbpedia-entity',
+    'fever',
+    'fiqa',
+    'hotpotqa',
+    'msmarco',
+    'nfcorpus',
+    'quora',
+    'scidocs',
+    'scifact',
+    'trec-covid',
+    'webis-touche2020',
+    'nq'
+]
+
+_DESCRIPTION = 'dataset load script for BEIR corpus'
+
+_DATASET_URLS = {
+    data: {
+        'train': f'https://huggingface.co/datasets/Tevatron/beir-corpus/resolve/main/{data}.jsonl.gz',
+    } for data in all_data
+}
+
+
+class BeirCorpus(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            version=datasets.Version('1.1.0'),
+            name=data, 
+            description=f'BEIR dataset corpus {data}.'
+        ) for data in all_data
+    ]
+
+    def _info(self):
+        features = datasets.Features({
+            'docid': datasets.Value('string'), 
+            'title': datasets.Value('string'),
+            'text': datasets.Value('string'),
+        })
+
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage='https://github.com/beir-cellar/beir',
+            # License for the dataset if available
+            license='',
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        data = self.config.name
+        downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[data])
+
+        splits = [
+            datasets.SplitGenerator(
+                name='train',
+                gen_kwargs={
+                    'filepath': downloaded_files['train'],
+                },
+            ),
+        ]
+        return splits
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for line in f:
+                data = json.loads(line)
+                if "_id" in data:
+                    data['docid'] = data.pop('_id')
+                yield data['docid'], data

climate-fever.jsonl.gz

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cqadupstack-physics.jsonl.gz

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