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:
+- expert-generated
+- found
+language_creators:
+- found
+languages:
+- en
+- yo
+licenses:
+- cc-by-4-0
+multilinguality:
+- translation
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
+---
+
+# Dataset Card for MENYO-20k
+
+## 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:** [Homepage for Menyo-20k](https://zenodo.org/record/4297448#.X81G7s0zZPY)
+- **Repository:**[Github Repo](https://github.com/dadelani/menyo-20k_MT)
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain)
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+Languages are English and YOruba
+
+## Dataset Structure
+
+### Data Instances
+
+The data consists of tab seperated entries
+
+```
+{'translation': 
+  {'en': 'Unit 1: What is Creative Commons?',
+  'yo': 'Ìdá 1: Kín ni Creative Commons?'
+  }
+}
+
+```
+
+### Data Fields
+
+- `en`: English sentence
+- `yo`: Yoruba sentence
+
+
+### Data Splits
+
+Only training dataset available
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+The dataset is open but for non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use.
+
+### Citation Information
+```
+@dataset{david_ifeoluwa_adelani_2020_4297448,
+  author       = {David Ifeoluwa Adelani and
+                  Jesujoba O. Alabi and
+                  Damilola Adebonojo and
+                  Adesina Ayeni and
+                  Mofe Adeyemi and
+                  Ayodele Awokoya},
+  title        = {{MENYO-20k: A Multi-domain English - Yorùbá Corpus 
+                   for Machine Translation}},
+  month        = nov,
+  year         = 2020,
+  publisher    = {Zenodo},
+  version      = {1.0},
+  doi          = {10.5281/zenodo.4297448},
+  url          = {https://doi.org/10.5281/zenodo.4297448}
+}
+```

dataset_infos.json

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+{"menyo20k_mt": {"description": "MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain). The development and test sets are available upon request.\n", "citation": "@dataset{david_ifeoluwa_adelani_2020_4297448,\n  author       = {David Ifeoluwa Adelani and\n                  Jesujoba O. Alabi and\n                  Damilola Adebonojo and\n                  Adesina Ayeni and\n                  Mofe Adeyemi and\n                  Ayodele Awokoya},\n  title        = {MENYO-20k: A Multi-domain English - Yor\u00f9b\u00e1 Corpus\n                  for Machine Translation},\n  month        = nov,\n  year         = 2020,\n  publisher    = {Zenodo},\n  version      = {1.0},\n  doi          = {10.5281/zenodo.4297448},\n  url          = {https://doi.org/10.5281/zenodo.4297448}\n}\n", "homepage": "https://zenodo.org/record/4297448#.X81G7s0zZPY", "license": "For non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use.", "features": {"translation": {"languages": ["en", "yo"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "builder_name": "menyo20k_mt", "config_name": "menyo20k_mt", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2551273, "num_examples": 10070, "dataset_name": "menyo20k_mt"}}, "download_checksums": {"https://github.com/dadelani/menyo-20k_MT/raw/main/data/train.tsv": {"num_bytes": 2490852, "checksum": "3c152119d4dc1fba12ee9424f1e7fd11648acfa8e2ea7f6464a37a18e69d9a06"}}, "download_size": 2490852, "post_processing_size": null, "dataset_size": 2551273, "size_in_bytes": 5042125}}

dummy/menyo20k_mt/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f9ef9bfa84a47a63b7581ea8594b5fbe58dbe49db50025beec1a3d6a78e02ecf
+size 869

menyo20k_mt.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.
+"""MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translations"""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+
+import datasets
+
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@dataset{david_ifeoluwa_adelani_2020_4297448,
+  author       = {David Ifeoluwa Adelani and
+                  Jesujoba O. Alabi and
+                  Damilola Adebonojo and
+                  Adesina Ayeni and
+                  Mofe Adeyemi and
+                  Ayodele Awokoya},
+  title        = {MENYO-20k: A Multi-domain English - Yorùbá Corpus
+                  for Machine Translation},
+  month        = nov,
+  year         = 2020,
+  publisher    = {Zenodo},
+  version      = {1.0},
+  doi          = {10.5281/zenodo.4297448},
+  url          = {https://doi.org/10.5281/zenodo.4297448}
+}
+"""
+
+
+# You can copy an official description
+_DESCRIPTION = """\
+MENYO-20k is a multi-domain parallel dataset with texts obtained from news articles, ted talks, movie transcripts, radio transcripts, science and technology texts, and other short articles curated from the web and professional translators. The dataset has 20,100 parallel sentences split into 10,070 training sentences, 3,397 development sentences, and 6,633 test sentences (3,419 multi-domain, 1,714 news domain, and 1,500 ted talks speech transcript domain). The development and test sets are available upon request.
+"""
+
+
+_HOMEPAGE = "https://zenodo.org/record/4297448#.X81G7s0zZPY"
+
+
+_LICENSE = "For non-commercial use because some of the data sources like Ted talks and JW news requires permission for commercial use."
+
+
+# The HuggingFace dataset library don't host the datasets but only point to the original files
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_URL = "https://github.com/dadelani/menyo-20k_MT/raw/main/data/train.tsv"
+
+
+class Menyo20kMt(datasets.GeneratorBasedBuilder):
+    """MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translations"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="menyo20k_mt",
+            version=VERSION,
+            description="MENYO-20k: A Multi-domain English - Yorùbá Corpus for Machine Translations",
+        )
+    ]
+
+    def _info(self):
+
+        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=datasets.Features({"translation": datasets.features.Translation(languages=("en", "yo"))}),
+            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."""
+        train_path = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for idx, row in enumerate(reader):
+                result = {"translation": {"en": row["English"], "yo": row["Yoruba"]}}
+                yield idx, result