Update files from the datasets library (from 1.2.0)

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

.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
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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- bg
+- cs
+- da
+- de
+- el
+- en
+- es
+- et
+- fi
+- fr
+- hr
+- hu
+- is
+- it
+- lt
+- lv
+- mt
+- nl
+- no
+- pl
+- pt
+- ro
+- ru
+- sk
+- sl
+- sq
+- sr
+- sv
+- tr
+- uk
+licenses:
+- cc-by-sa-4-0
+multilinguality:
+- multilingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
+---
+
+# Dataset Card Creation Guide
+
+## 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:** http://opus.nlpl.eu/TildeMODEL.php
+- **Repository:** None
+- **Paper:** https://www.aclweb.org/anthology/W17-0235.pdf
+- **Leaderboard:** [More Information Needed]
+- **Point of Contact:** [More Information Needed]
+
+### Dataset Summary
+
+To load a language pair which isn't part of the config, all you need to do is specify the language code as pairs.
+You can find the valid pairs in Homepage section of Dataset Description: http://opus.nlpl.eu/TildeMODEL.php
+E.g.
+
+`dataset = load_dataset("tilde_model", lang1="en", lang2="lv")`
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+Here are some examples of questions and facts:
+
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### 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
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"bg-el": {"description": "This is the Tilde MODEL Corpus \u2013 Multilingual Open Data for European Languages.\n\nThe data has been collected from sites allowing free use and reuse of its content, as well as from Public Sector web sites. The activities have been undertaken as part of the ODINE Open Data Incubator for Europe, which aims to support the next generation of digital businesses and fast-track the development of new products and services. The corpus includes the following parts:\nTilde MODEL - EESC is a multilingual corpus compiled from document texts of European Economic and Social Committee document portal. Source: http://dm.eesc.europa.eu/\nTilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/\nTilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/\nTilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016\nTilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017\nTilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017\nTilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017\nTilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017\nTilde MODEL - mupa.hu is a parallel corpus from texts of M\u00fcpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017\nTilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017\nTilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017\n30 languages, 274 bitexts\ntotal number of files: 125\ntotal number of tokens: 1.43G\ntotal number of sentence fragments: 62.44M\n", "citation": "Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. Proceedings of the 21th Nordic Conference of Computational Linguistics NODALIDA 2017\n", "homepage": "http://opus.nlpl.eu/TildeMODEL.php", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "translation": {"languages": ["bg", "el"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "builder_name": "tilde_model", "config_name": "bg-el", "version": {"version_str": "2018.0.0", "description": "", "major": 2018, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 258081, "num_examples": 455, "dataset_name": "tilde_model"}}, "download_checksums": {"https://object.pouta.csc.fi/OPUS-TildeMODEL/v2018/moses/bg-el.txt.zip": {"num_bytes": 64430, "checksum": "71edf70d4ab1d2c66d6e350b699d861978cf3e132e410be02636ebfdfd062a49"}}, "download_size": 64430, "post_processing_size": null, "dataset_size": 258081, "size_in_bytes": 322511}, "cs-en": {"description": "This is the Tilde MODEL Corpus \u2013 Multilingual Open Data for European Languages.\n\nThe data has been collected from sites allowing free use and reuse of its content, as well as from Public Sector web sites. 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Source: http://dm.eesc.europa.eu/\nTilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/\nTilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/\nTilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016\nTilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017\nTilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017\nTilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017\nTilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017\nTilde MODEL - mupa.hu is a parallel corpus from texts of M\u00fcpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017\nTilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017\nTilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017\n30 languages, 274 bitexts\ntotal number of files: 125\ntotal number of tokens: 1.43G\ntotal number of sentence fragments: 62.44M\n", "citation": "Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. Proceedings of the 21th Nordic Conference of Computational Linguistics NODALIDA 2017\n", "homepage": "http://opus.nlpl.eu/TildeMODEL.php", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "translation": {"languages": ["cs", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": null, "builder_name": "tilde_model", "config_name": "cs-en", "version": {"version_str": "2018.0.0", "description": "", "major": 2018, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 709168, "num_examples": 3100, "dataset_name": "tilde_model"}}, "download_checksums": {"https://object.pouta.csc.fi/OPUS-TildeMODEL/v2018/moses/cs-en.txt.zip": {"num_bytes": 201503, "checksum": "e2cf71f0056c36c96715509e035168b4e81ced9d4644f48fdb15d5358cb1d168"}}, "download_size": 201503, "post_processing_size": null, "dataset_size": 709168, "size_in_bytes": 910671}, "de-hr": {"description": "This is the Tilde MODEL Corpus \u2013 Multilingual Open Data for European Languages.\n\nThe data has been collected from sites allowing free use and reuse of its content, as well as from Public Sector web sites. 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Source: http://dm.eesc.europa.eu/\nTilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/\nTilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/\nTilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016\nTilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017\nTilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017\nTilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017\nTilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017\nTilde MODEL - mupa.hu is a parallel corpus from texts of M\u00fcpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017\nTilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017\nTilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017\n30 languages, 274 bitexts\ntotal number of files: 125\ntotal number of tokens: 1.43G\ntotal number of sentence fragments: 62.44M\n", "citation": "Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. 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Source: http://dm.eesc.europa.eu/\nTilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/\nTilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/\nTilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016\nTilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017\nTilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017\nTilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017\nTilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017\nTilde MODEL - mupa.hu is a parallel corpus from texts of M\u00fcpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017\nTilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017\nTilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017\n30 languages, 274 bitexts\ntotal number of files: 125\ntotal number of tokens: 1.43G\ntotal number of sentence fragments: 62.44M\n", "citation": "Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. 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Source: http://dm.eesc.europa.eu/\nTilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/\nTilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/\nTilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016\nTilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017\nTilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017\nTilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017\nTilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017\nTilde MODEL - mupa.hu is a parallel corpus from texts of M\u00fcpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017\nTilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017\nTilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017\n30 languages, 274 bitexts\ntotal number of files: 125\ntotal number of tokens: 1.43G\ntotal number of sentence fragments: 62.44M\n", "citation": "Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. 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tilde_model.py

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+# coding=utf-8
+# Copyright 2020 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
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+This is the Tilde MODEL Corpus – Multilingual Open Data for European Languages.
+
+The data has been collected from sites allowing free use and reuse of its content, as well as from Public Sector web sites. The activities have been undertaken as part of the ODINE Open Data Incubator for Europe, which aims to support the next generation of digital businesses and fast-track the development of new products and services. The corpus includes the following parts:
+Tilde MODEL - EESC is a multilingual corpus compiled from document texts of European Economic and Social Committee document portal. Source: http://dm.eesc.europa.eu/
+Tilde MODEL - RAPID multilingual parallel corpus is compiled from all press releases of Press Release Database of European Commission released between 1975 and end of 2016 as available from http://europa.eu/rapid/
+Tilde MODEL - ECB multilingual parallel corpus is compiled from the multilingual pages of European Central Bank web site http://ebc.europa.eu/
+Tilde MODEL - EMA is a corpus compiled from texts of European Medicines Agency document portal as available in http://www.ema.europa.eu/ at the end of 2016
+Tilde MODEL - World Bank is a corpus compiled from texts of World Bank as available in http://www.worldbank.org/ in 2017
+Tilde MODEL - AirBaltic.com Travel Destinations is a multilingual parallel corpus compiled from description texts of AirBaltic.com travel destinations as available in https://www.airbaltic.com/en/destinations/ in 2017
+Tilde MODEL - LiveRiga.com is a multilingual parallel corpus compiled from Riga tourist attractions description texts of http://liveriga.com/ web site in 2017
+Tilde MODEL - Lithuanian National Philharmonic Society is a parallel corpus compiled from texts of Lithuanian National Philharmonic Society web site http://www.filharmonija.lt/ in 2017
+Tilde MODEL - mupa.hu is a parallel corpus from texts of Müpa Budapest - web site of Hungarian national culture house and concert venue https://www.mupa.hu/en/ compiled in spring of 2017
+Tilde MODEL - fold.lv is a parallel corpus from texts of fold.lv portal http://www.fold.lv/en/ of the best of Latvian and foreign creative industries as compiled in spring of 2017
+Tilde MODEL - czechtourism.com is a multilingual parallel corpus from texts of http://czechtourism.com/ portal compiled in spring of 2017
+30 languages, 274 bitexts
+total number of files: 125
+total number of tokens: 1.43G
+total number of sentence fragments: 62.44M
+"""
+_HOMEPAGE_URL = "http://opus.nlpl.eu/TildeMODEL.php"
+_CITATION = """\
+Roberts Rozis, Raivis Skadins, 2017, Tilde MODEL - Multilingual Open Data for EU Languages. Proceedings of the 21th Nordic Conference of Computational Linguistics NODALIDA 2017
+"""
+
+_VERSION = "2018.0.0"
+_BASE_NAME = "TildeMODEL.{}.{}"
+_BASE_URL = "https://object.pouta.csc.fi/OPUS-TildeMODEL/v2018/moses/{}-{}.txt.zip"
+
+# Please note that only few pairs are shown here. You can use config to generate data for all language pairs
+_LANGUAGE_PAIRS = [
+    ("bg", "el"),
+    ("cs", "en"),
+    ("de", "hr"),
+    ("en", "no"),
+    ("es", "pt"),
+]
+
+
+class TildeModelConfig(datasets.BuilderConfig):
+    def __init__(self, *args, lang1=None, lang2=None, **kwargs):
+        super().__init__(
+            *args,
+            name=f"{lang1}-{lang2}",
+            **kwargs,
+        )
+        self.lang1 = lang1
+        self.lang2 = lang2
+
+
+class TildeModel(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        TildeModelConfig(
+            lang1=lang1,
+            lang2=lang2,
+            description=f"Translating {lang1} to {lang2} or vice versa",
+            version=datasets.Version(_VERSION),
+        )
+        for lang1, lang2 in _LANGUAGE_PAIRS
+    ]
+    BUILDER_CONFIG_CLASS = TildeModelConfig
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
+                },
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        def _base_url(lang1, lang2):
+            return _BASE_URL.format(lang1, lang2)
+
+        download_url = _base_url(self.config.lang1, self.config.lang2)
+        path = dl_manager.download_and_extract(download_url)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"datapath": path},
+            )
+        ]
+
+    def _generate_examples(self, datapath):
+        l1, l2 = self.config.lang1, self.config.lang2
+        folder = l1 + "-" + l2
+        l1_file = _BASE_NAME.format(folder, l1)
+        l2_file = _BASE_NAME.format(folder, l2)
+        l1_path = os.path.join(datapath, l1_file)
+        l2_path = os.path.join(datapath, l2_file)
+        with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2:
+            for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
+                x = x.strip()
+                y = y.strip()
+                result = (
+                    sentence_counter,
+                    {
+                        "id": str(sentence_counter),
+                        "translation": {l1: x, l2: y},
+                    },
+                )
+                yield result