Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+- machine-generated
+languages:
+- sv
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- extended|other-sts-b
+task_categories:
+- text-scoring
+task_ids:
+- semantic-similarity-scoring
+---
+
+# Dataset Card for Swedish Machine Translated STS-B 
+
+## 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:** [stsb-mt-sv homepage](https://github.com/timpal0l/sts-benchmark-swedish)
+- **Repository:** [stsb-mt-sv repository](https://github.com/timpal0l/sts-benchmark-swedish)
+- **Paper:** [Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
+](https://arxiv.org/abs/2009.03116)
+- **Point of Contact:** [Tim Isbister](mailto:timisbisters@gmail.com)
+
+### Dataset Summary
+
+This dataset is a Swedish machine translated version for semantic textual similarity. 
+
+### Supported Tasks and Leaderboards
+
+This dataset can be used to evaluate text similarity on Swedish.
+
+### Languages
+
+The text in the dataset is in Swedish. The associated BCP-47 code is `sv`.
+
+## Dataset Structure
+
+### Data Instances
+
+What a sample looks like:
+```
+{'score': '4.2',
+ 'sentence1': 'Undrar om jultomten kommer i år pga Corona..?',
+ 'sentence2': 'Jag undrar om jultomen kommer hit i år med tanke på covid-19',
+}
+```
+
+### Data Fields
+
+- `score`: a float representing the semantic similarity score. Where 0.0 is the lowest score and 5.0 is the highest.
+- `sentence1`: a string representing a text
+- `sentence2`: another string to compare the semantic with
+
+### Data Splits
+
+The data is split into a training, validation and test set. The final split sizes are as follow:
+
+| Train  | Valid | Test |
+| ------ | ----- | ---- |
+| 5749   |  1500 | 1379 |
+
+## Dataset Creation
+
+### Curation Rationale
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+#### Who are the source language producers?
+
+### Annotations
+
+#### Annotation process
+
+#### Who are the annotators?
+
+### Personal and Sensitive Information
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+### Discussion of Biases
+
+### Other Known Limitations
+
+## Additional Information
+
+### Dataset Curators
+
+The machine translated version were put together by @timpal0l
+
+### Licensing Information
+
+### Citation Information
+
+```
+@article{isbister2020not,
+  title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity},
+  author={Isbister, Tim and Sahlgren, Magnus},
+  journal={arXiv preprint arXiv:2009.03116},
+  year={2020}
+}
+```

dataset_infos.json

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+{"plain_text": {"description": "Machine translated Swedish version of the original STS-B (http://ixa2.si.ehu.eus/stswiki)", "citation": "@article{isbister2020not,\n  title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity},\n  author={Isbister, Tim and Sahlgren, Magnus},\n  journal={arXiv preprint arXiv:2009.03116},\n  year={2020}\n}\n", "homepage": "https://github.com/timpal0l/sts-benchmark-swedish", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "score": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "stsb_mt_sv", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 171823, "num_examples": 1379, "dataset_name": "stsb_mt_sv"}, "validation": {"name": "validation", "num_bytes": 218843, "num_examples": 1500, "dataset_name": "stsb_mt_sv"}, "train": {"name": "train", "num_bytes": 772847, "num_examples": 5749, "dataset_name": "stsb_mt_sv"}}, "download_checksums": {"https://raw.githubusercontent.com/timpal0l/sts-benchmark-swedish/master/data/stsb-mt-sv.zip": {"num_bytes": 383047, "checksum": "f7f941887a6fea53efa4379c0a5338ee0ea0b704debabbd2dd8dec9c2ef4891f"}}, "download_size": 383047, "post_processing_size": null, "dataset_size": 1163513, "size_in_bytes": 1546560}}

dummy/plain_text/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:350ac3546ce3803fc8603d0da0a08475742a883ba5fb0c4046f923b3e9877b3a
+size 1250

stsb_mt_sv.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# 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
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+
+import datasets
+
+
+_DOWNLOAD_URL = "https://raw.githubusercontent.com/timpal0l/sts-benchmark-swedish/master/data/stsb-mt-sv.zip"
+_TRAIN_FILE = "train-sv.tsv"
+_VAL_FILE = "dev-sv.tsv"
+_TEST_FILE = "test-sv.tsv"
+
+_CITATION = """\
+@article{isbister2020not,
+  title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity},
+  author={Isbister, Tim and Sahlgren, Magnus},
+  journal={arXiv preprint arXiv:2009.03116},
+  year={2020}
+}
+"""
+
+_DESCRIPTION = "Machine translated Swedish version of the original STS-B (http://ixa2.si.ehu.eus/stswiki)"
+
+
+class StsbMtSv(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of the Swedish Machine Translated STS-B",
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence1": datasets.Value("string"),
+                    "sentence2": datasets.Value("string"),
+                    "score": datasets.Value("float"),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://github.com/timpal0l/sts-benchmark-swedish",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": os.path.join(dl_dir, _TEST_FILE)},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": os.path.join(dl_dir, _VAL_FILE)},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": os.path.join(dl_dir, _TRAIN_FILE)},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for idx, row in enumerate(reader):
+                yield idx, {
+                    "sentence1": row["sentence1"],
+                    "sentence2": row["sentence2"],
+                    "score": row["score"],
+                }