Update files from the datasets library (from 1.4.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.4.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+annotations_creators:
+- crowdsourced
+- machine-generated
+language_creators:
+- found
+languages:
+- en
+licenses:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+  default:
+  - 10K<n<100K
+  pid2name:
+  - n<1K
+source_datasets:
+- original
+task_categories:
+- other
+task_ids:
+- other-other-relation-extraction
+---
+
+# Dataset Card for few_rel
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [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)
+
+## Dataset Description
+
+- **Homepage:** [GitHub Page](https://thunlp.github.io/)
+- **Repository:** [GitHub](https://github.com/thunlp/FewRel)
+- **Paper:** [FewRel](https://www.aclweb.org/anthology/D18-1514.pdf), [FewRel 2.0](https://www.aclweb.org/anthology/D19-1649.pdf)
+- **Leaderboard:** [GitHub Leaderboard](https://thunlp.github.io/fewrel.html)
+- **Point of Contact:** [Needs More Information]
+
+### Dataset Summary
+
+FewRel is a large-scale few-shot relation extraction dataset, which contains more than one hundred relations and tens of thousands of annotated instances cross different domains.
+
+### Supported Tasks and Leaderboards
+
+[Needs More Information]
+
+### Languages
+
+The dataset contaings English text, as used by writers on Wikipedia, and crowdsourced English annotations.
+
+## Dataset Structure
+
+
+### Data Instances
+
+An instance from `train_wiki` split:
+
+```
+{'head': {'indices': [[16]], 'text': 'tjq', 'type': 'Q1331049'}, 'names': ['place served by transport hub', 'territorial entity or entities served by this transport hub (airport, train station, etc.)'], 'relation': 'P931', 'tail': {'indices': [[13, 14]], 'text': 'tanjung pandan', 'type': 'Q3056359'}, 'tokens': ['Merpati', 'flight', '106', 'departed', 'Jakarta', '(', 'CGK', ')', 'on', 'a', 'domestic', 'flight', 'to', 'Tanjung', 'Pandan', '(', 'TJQ', ')', '.']}
+```
+
+### Data Fields
+
+For `default`:
+
+- `relation`: a `string` feature containing PID of the relation.
+- `tokens`: a `list` of `string` features containing tokens for the text.
+- `head`: a dictionary containing:
+  - `text`: a `string` feature representing the head entity.
+  - `type`: a `string` feature representing the type of the head entity.
+  - `indices`: a `list` containing `list` of token indices.
+
+- `tail`: a dictionary containing:
+  - `text`: a `string` feature representing the tail entity.
+  - `type`: a `string` feature representing the type of the tail entity.
+  - `indices`: a `list` containing `list` of token indices.
+- `names`: a `list` of `string` features containing relation names. For `pubmed_unsupervised` split, this is set to a `list` with an empty `string`. For `val_semeval` and `val_pubmed` split, this is set to a `list` with the `string` from the `relation` field.
+
+### Data Splits
+
+`train_wiki`: 44800
+`val_nyt`: 2500
+`val_pubmed`: 1000
+`val_semeval`: 8851
+`val_wiki`: 11200
+`pubmed_unsupervised`: 2500
+
+## Dataset Creation
+
+### Curation Rationale
+
+[Needs More Information]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[Needs More Information]
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+[Needs More Information]
+
+### Personal and Sensitive Information
+
+[Needs More Information]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Needs More Information]
+
+### Discussion of Biases
+
+[Needs More Information]
+
+### Other Known Limitations
+
+[Needs More Information]
+
+## Additional Information
+
+### Dataset Curators
+
+For FewRel:
+
+Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong
+
+For  FewRel 2.0:
+
+Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie
+
+### Licensing Information
+
+```
+MIT License
+
+Copyright (c) 2018 THUNLP
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+```
+
+### Citation Information
+
+```
+@inproceedings{han-etal-2018-fewrel,
+    title = "{F}ew{R}el: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation",
+    author = "Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong",
+    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
+    month = oct # "-" # nov,
+    year = "2018",
+    address = "Brussels, Belgium",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D18-1514",
+    doi = "10.18653/v1/D18-1514",
+    pages = "4803--4809"
+}
+```
+```
+
+@inproceedings{gao-etal-2019-fewrel,
+    title = "{F}ew{R}el 2.0: Towards More Challenging Few-Shot Relation Classification",
+    author = "Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
+    month = nov,
+    year = "2019",
+    address = "Hong Kong, China",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D19-1649",
+    doi = "10.18653/v1/D19-1649",
+    pages = "6251--6256"
+}
+```
+
+### Contributions
+
+Thanks to [@gchhablani](https://github.com/gchhablani) for adding this dataset.

dataset_infos.json

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dummy/default/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f73aa3427b81fbed9ec55e0bbd8d60b8b375dff12d18def5ffe97290227e86cf
+size 6859

few_rel.py

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+# 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.
+"""FewRel Dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+
+import datasets
+
+
+_CITATION = """@inproceedings{han-etal-2018-fewrel,
+    title = "{F}ew{R}el: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation",
+    author = "Han, Xu and Zhu, Hao and Yu, Pengfei and Wang, Ziyun and Yao, Yuan and Liu, Zhiyuan and Sun, Maosong",
+    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
+    month = oct # "-" # nov,
+    year = "2018",
+    address = "Brussels, Belgium",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D18-1514",
+    doi = "10.18653/v1/D18-1514",
+    pages = "4803--4809"
+}
+
+@inproceedings{gao-etal-2019-fewrel,
+    title = "{F}ew{R}el 2.0: Towards More Challenging Few-Shot Relation Classification",
+    author = "Gao, Tianyu and Han, Xu and Zhu, Hao and Liu, Zhiyuan and Li, Peng and Sun, Maosong and Zhou, Jie",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
+    month = nov,
+    year = "2019",
+    address = "Hong Kong, China",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/D19-1649",
+    doi = "10.18653/v1/D19-1649",
+    pages = "6251--6256"
+}
+"""
+
+_DESCRIPTION = """\
+FewRel is a large-scale few-shot relation extraction dataset, which contains more than one hundred relations and tens of thousands of annotated instances cross different domains.
+"""
+
+_HOMEPAGE = "https://thunlp.github.io/"
+
+_LICENSE = "https://raw.githubusercontent.com/thunlp/FewRel/master/LICENSE"
+
+DATA_URL = "https://raw.githubusercontent.com/thunlp/FewRel/master/data/"
+_URLs = {
+    "train_wiki": DATA_URL + "train_wiki.json",
+    "val_nyt": DATA_URL + "val_nyt.json",
+    "val_pubmed": DATA_URL + "val_pubmed.json",
+    "val_semeval": DATA_URL + "val_semeval.json",
+    "val_wiki": DATA_URL + "val_wiki.json",
+    "pid2name": DATA_URL + "pid2name.json",
+    "pubmed_unsupervised": DATA_URL + "pubmed_unsupervised.json",
+}
+
+
+class FewRel(datasets.GeneratorBasedBuilder):
+    """The FewRelDataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="default", version=VERSION, description="This covers the entire FewRel dataset."),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "relation": datasets.Value("string"),
+                "tokens": datasets.Sequence(datasets.Value("string")),
+                "head": {
+                    "text": datasets.Value("string"),
+                    "type": datasets.Value("string"),
+                    "indices": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
+                },
+                "tail": {
+                    "text": datasets.Value("string"),
+                    "type": datasets.Value("string"),
+                    "indices": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
+                },
+                "names": datasets.Sequence(datasets.Value("string"))
+                # These are the features of your dataset like images, labels ...
+            }
+        )
+
+        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
+            # 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=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split(key),
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": data_dir[key],
+                    "pid2name": data_dir["pid2name"],
+                    "return_names": key in ["train_wiki", "val_wiki", "val_nyt"],
+                },
+            )
+            for key in data_dir.keys()
+            if key != "pid2name"
+        ]
+
+    def _generate_examples(self, filepath, pid2name, return_names):
+        """ Yields examples. """
+        pid2name_dict = {}
+        with open(pid2name, encoding="utf-8") as f:
+            data = json.load(f)
+        for key in list(data.keys()):
+            name_1 = data[key][0]
+            name_2 = data[key][1]
+            pid2name_dict[key] = [name_1, name_2]
+
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            # print(data)
+        if isinstance(data, dict):
+            id = 0
+            for key in list(data.keys()):
+                for items in data[key]:
+                    tokens = items["tokens"]
+                    h_0 = items["h"][0]
+                    h_1 = items["h"][1]
+                    h_2 = items["h"][2]
+                    t_0 = items["t"][0]
+                    t_1 = items["t"][1]
+                    t_2 = items["t"][2]
+                    id += 1
+                    yield id, {
+                        "relation": key,
+                        "tokens": tokens,
+                        "head": {"text": h_0, "type": h_1, "indices": h_2},
+                        "tail": {"text": t_0, "type": t_1, "indices": t_2},
+                        "names": pid2name_dict[key]
+                        if return_names
+                        else [
+                            key,
+                        ],
+                    }
+        else:  # For `pubmed_unsupervised.json`
+            id = 0
+            for items in data:
+                tokens = items["tokens"]
+                h_0 = items["h"][0]
+                h_1 = items["h"][1]
+                h_2 = items["h"][2]
+                t_0 = items["t"][0]
+                t_1 = items["t"][1]
+                t_2 = items["t"][2]
+                id += 1
+                yield id, {
+                    "relation": "",
+                    "tokens": tokens,
+                    "head": {"text": h_0, "type": h_1, "indices": h_2},
+                    "tail": {"text": t_0, "type": t_1, "indices": t_2},
+                    "names": [
+                        "",
+                    ],
+                }