Update files from the datasets library (from 1.16.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.16.0

README.md

@@ -1,5 +1,12 @@
 ---
+pretty_name: WMT15
 paperswithcode_id: wmt-2015
+multilinguality:
+- translation
+task_categories:
+- conditional-text-generation
+task_ids:
+- machine-translation
 ---
 
 # Dataset Card for "wmt15"

dataset_infos.json

@@ -1 +1 @@
-{"cs-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["cs", "en"], "id": null, "_type": "Translation"}}, "supervised_keys": {"input": "cs", "output": "en"}, "builder_name": "wmt15", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 572203, "num_examples": 2656, "dataset_name": "wmt15"}, "train": {"name": "train", "num_bytes": 283007221, "num_examples": 959768, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 757817, "num_examples": 3003, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-europarl-v7.tgz": {"num_bytes": 657632379, "checksum": "0224c7c710c8a063dfd893b0cc0830202d61f4c75c17eb8e31836103d27d96e7"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-commoncrawl.tgz": {"num_bytes": 918311367, "checksum": "c7a74e2ea01ac6c920123108627e35278d4ccb5701e15428ffa34de86fa3a9e5"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main/training-parallel-nc-v10.tgz": {"num_bytes": 125136590, "checksum": "11e053e7ea29e87e69a1ad05e61cb559820947ecec144ea8c1d6cf05017c9602"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz": {"num_bytes": 38654961, "checksum": "7a7deccf82ebb05ba508dba5eb21356492224e8f630ec4f992132b029b4b25e7"}}, "download_size": 1739735297, "dataset_size": 284337241, "size_in_bytes": 2024072538}}
+{"cs-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["cs", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "cs", "output": "en"}, "task_templates": null, "builder_name": "wmt15", "config_name": "cs-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 282996942, "num_examples": 959768, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 757817, "num_examples": 3003, "dataset_name": "wmt15"}, "test": {"name": "test", "num_bytes": 572203, "num_examples": 2656, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip": {"num_bytes": 125125074, "checksum": "fc54b5efb6ea48a6f16aea4c2c45882033d5e11108369f4ff82be692bd8ee7b5"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1740666258, "post_processing_size": null, "dataset_size": 284326962, "size_in_bytes": 2024993220}, "de-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["de", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "de", "output": "en"}, "task_templates": null, "builder_name": "wmt15", "config_name": "de-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1364002869, "num_examples": 4522998, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 777334, "num_examples": 3003, "dataset_name": "wmt15"}, "test": {"name": "test", "num_bytes": 522989, "num_examples": 2169, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip": {"num_bytes": 125125074, "checksum": "fc54b5efb6ea48a6f16aea4c2c45882033d5e11108369f4ff82be692bd8ee7b5"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1740666258, "post_processing_size": null, "dataset_size": 1365303192, "size_in_bytes": 3105969450}, "fi-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["fi", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "fi", "output": "en"}, "task_templates": null, "builder_name": "wmt15", "config_name": "fi-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 605146817, "num_examples": 2073394, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 363941, "num_examples": 1500, "dataset_name": "wmt15"}, "test": {"name": "test", "num_bytes": 306335, "num_examples": 1370, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-ep-v8.zip": {"num_bytes": 225190342, "checksum": "387e570a6812948e30c64885e64a1d3735a66b7c0bc424fcff1208ef11110149"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip": {"num_bytes": 9485604, "checksum": "b3134566261b39d830eed345df1be1864039339cfeccf24b1bf86398c9e4a87c"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 273390220, "post_processing_size": null, "dataset_size": 605817093, "size_in_bytes": 879207313}, "fr-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["fr", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "fr", "output": "en"}, "task_templates": null, "builder_name": "wmt15", "config_name": "fr-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 14758986622, "num_examples": 40853137, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 1138737, "num_examples": 4503, "dataset_name": "wmt15"}, "test": {"name": "test", "num_bytes": 298771, "num_examples": 1500, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip": {"num_bytes": 658092427, "checksum": "5b2d8b32c2396da739b4e731871c597fcc6e75729becd74619d0712eecf7770e"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip": {"num_bytes": 2366237633, "checksum": "74f07002e053c81bc7f73b4fdab58e7987e831338748f264cbda82a8b062d2e2"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip": {"num_bytes": 125125074, "checksum": "fc54b5efb6ea48a6f16aea4c2c45882033d5e11108369f4ff82be692bd8ee7b5"}, "https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip": {"num_bytes": 2595877717, "checksum": "9439f86523e5dff3f923526dbf6c6929da1786c18dbf64436d2b7564b83aaba3"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 6702781608, "post_processing_size": null, "dataset_size": 14760424130, "size_in_bytes": 21463205738}, "ru-en": {"description": "Translate dataset based on the data from statmt.org.\n\nVersions exists for the different years using a combination of multiple data\nsources. The base `wmt_translate` allows you to create your own config to choose\nyour own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\n\n```\nconfig = datasets.wmt.WmtConfig(\n    version=\"0.0.1\",\n    language_pair=(\"fr\", \"de\"),\n    subsets={\n        datasets.Split.TRAIN: [\"commoncrawl_frde\"],\n        datasets.Split.VALIDATION: [\"euelections_dev2019\"],\n    },\n)\nbuilder = datasets.builder(\"wmt_translate\", config=config)\n```\n\n", "citation": "\n@InProceedings{bojar-EtAl:2015:WMT,\n  author    = {Bojar, Ond\u000b{r}ej  and  Chatterjee, Rajen  and  Federmann, Christian  and  Haddow, Barry  and  Huck, Matthias  and  Hokamp, Chris  and  Koehn, Philipp  and  Logacheva, Varvara  and  Monz, Christof  and  Negri, Matteo  and  Post, Matt  and  Scarton, Carolina  and  Specia, Lucia  and  Turchi, Marco},\n  title     = {Findings of the 2015 Workshop on Statistical Machine Translation},\n  booktitle = {Proceedings of the Tenth Workshop on Statistical Machine Translation},\n  month     = {September},\n  year      = {2015},\n  address   = {Lisbon, Portugal},\n  publisher = {Association for Computational Linguistics},\n  pages     = {1--46},\n  url       = {http://aclweb.org/anthology/W15-3001}\n}\n", "homepage": "http://www.statmt.org/wmt15/translation-task.html", "license": "", "features": {"translation": {"languages": ["ru", "en"], "id": null, "_type": "Translation"}}, "post_processed": null, "supervised_keys": {"input": "ru", "output": "en"}, "task_templates": null, "builder_name": "wmt15", "config_name": "ru-en", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 437752256, "num_examples": 1495081, "dataset_name": "wmt15"}, "validation": {"name": "validation", "num_bytes": 1087746, "num_examples": 3003, "dataset_name": "wmt15"}, "test": {"name": "test", "num_bytes": 955972, "num_examples": 2818, "dataset_name": "wmt15"}}, "download_checksums": {"https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip": {"num_bytes": 918734483, "checksum": "5ffe980072ea29adfd84568d099bea366d9f72772b988e670794ae851b4e5627"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip": {"num_bytes": 125125074, "checksum": "fc54b5efb6ea48a6f16aea4c2c45882033d5e11108369f4ff82be692bd8ee7b5"}, "https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip": {"num_bytes": 9485604, "checksum": "b3134566261b39d830eed345df1be1864039339cfeccf24b1bf86398c9e4a87c"}, "https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip": {"num_bytes": 38714274, "checksum": "d796e363740fdc4261aa6f5a3d2f8223e3adaee7d737b7724863325b8956dfd1"}}, "download_size": 1092059435, "post_processing_size": null, "dataset_size": 439795974, "size_in_bytes": 1531855409}}

dummy/cs-en/1.0.0/dummy_data.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:71ce11fc038d3a1fdca3050fb0753134e670dc8f3967f1951199d56ed7021fc7
-size 4624
+oid sha256:95ab846169cd72aebb71ef76b68e836d7a1c83ce7eadf7f234ee895b8dfa01bb
+size 6179

wmt_utils.py

@@ -96,7 +96,7 @@ class SubDataset:
     def _inject_language(self, src, strings):
         """Injects languages into (potentially) template strings."""
         if src not in self.sources:
-            raise ValueError("Invalid source for '{0}': {1}".format(self.name, src))
+            raise ValueError(f"Invalid source for '{self.name}': {src}")
 
         def _format_string(s):
             if "{0}" in s and "{1}" and "{src}" in s:
@@ -127,7 +127,7 @@ _TRAIN_SUBSETS = [
         name="commoncrawl",
         target="en",  # fr-de pair in commoncrawl_frde
         sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-commoncrawl.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-commoncrawl.zip",
         path=("commoncrawl.{src}-en.{src}", "commoncrawl.{src}-en.en"),
     ),
     SubDataset(
@@ -184,14 +184,14 @@ _TRAIN_SUBSETS = [
         name="dcep_v1",
         target="en",
         sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/dcep.lv-en.v1.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/dcep.lv-en.v1.zip",
         path=("dcep.en-lv/dcep.lv", "dcep.en-lv/dcep.en"),
     ),
     SubDataset(
         name="europarl_v7",
         target="en",
         sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-europarl-v7.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-europarl-v7.zip",
         path=("training/europarl-v7.{src}-en.{src}", "training/europarl-v7.{src}-en.en"),
     ),
     SubDataset(
@@ -208,14 +208,14 @@ _TRAIN_SUBSETS = [
         name="europarl_v8_18",
         target="en",
         sources={"et", "fi"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/training-parallel-ep-v8.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
         path=("training/europarl-v8.{src}-en.{src}", "training/europarl-v8.{src}-en.en"),
     ),
     SubDataset(
         name="europarl_v8_16",
         target="en",
         sources={"fi", "ro"},
-        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main/translation-task/training-parallel-ep-v8.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-ep-v8.zip",
         path=("training-parallel-ep-v8/europarl-v8.{src}-en.{src}", "training-parallel-ep-v8/europarl-v8.{src}-en.en"),
     ),
     SubDataset(
@@ -229,7 +229,7 @@ _TRAIN_SUBSETS = [
         name="gigafren",
         target="en",
         sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt10/resolve/main/training-giga-fren.tar",
+        url="https://huggingface.co/datasets/wmt/wmt10/resolve/main-zip/training-giga-fren.zip",
         path=("giga-fren.release2.fixed.fr.gz", "giga-fren.release2.fixed.en.gz"),
     ),
     SubDataset(
@@ -244,35 +244,35 @@ _TRAIN_SUBSETS = [
         name="leta_v1",
         target="en",
         sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/leta.v1.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/leta.v1.zip",
         path=("LETA-lv-en/leta.lv", "LETA-lv-en/leta.en"),
     ),
     SubDataset(
         name="multiun",
         target="en",
         sources={"es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main/training-parallel-un.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt13/resolve/main-zip/training-parallel-un.zip",
         path=("un/undoc.2000.{src}-en.{src}", "un/undoc.2000.{src}-en.en"),
     ),
     SubDataset(
         name="newscommentary_v9",
         target="en",
         sources={"cs", "de", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main/training-parallel-nc-v9.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/training-parallel-nc-v9.zip",
         path=("training/news-commentary-v9.{src}-en.{src}", "training/news-commentary-v9.{src}-en.en"),
     ),
     SubDataset(
         name="newscommentary_v10",
         target="en",
         sources={"cs", "de", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/training-parallel-nc-v10.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/training-parallel-nc-v10.zip",
         path=("news-commentary-v10.{src}-en.{src}", "news-commentary-v10.{src}-en.en"),
     ),
     SubDataset(
         name="newscommentary_v11",
         target="en",
         sources={"cs", "de", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main/translation-task/training-parallel-nc-v11.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt16/resolve/main-zip/translation-task/training-parallel-nc-v11.zip",
         path=(
             "training-parallel-nc-v11/news-commentary-v11.{src}-en.{src}",
             "training-parallel-nc-v11/news-commentary-v11.{src}-en.en",
@@ -282,14 +282,14 @@ _TRAIN_SUBSETS = [
         name="newscommentary_v12",
         target="en",
         sources={"cs", "de", "ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/training-parallel-nc-v12.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/training-parallel-nc-v12.zip",
         path=("training/news-commentary-v12.{src}-en.{src}", "training/news-commentary-v12.{src}-en.en"),
     ),
     SubDataset(
         name="newscommentary_v13",
         target="en",
         sources={"cs", "de", "ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/training-parallel-nc-v13.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/training-parallel-nc-v13.zip",
         path=(
             "training-parallel-nc-v13/news-commentary-v13.{src}-en.{src}",
             "training-parallel-nc-v13/news-commentary-v13.{src}-en.en",
@@ -313,14 +313,14 @@ _TRAIN_SUBSETS = [
         name="onlinebooks_v1",
         target="en",
         sources={"lv"},
-        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main/translation-task/books.lv-en.v1.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt17/resolve/main-zip/translation-task/books.lv-en.v1.zip",
         path=("farewell/farewell.lv", "farewell/farewell.en"),
     ),
     SubDataset(
         name="paracrawl_v1",
         target="en",
         sources={"cs", "de", "et", "fi", "ru"},
-        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz",
+        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-{src}.zipporah0-dedup-clean.tgz",  # TODO(QL): use gzip for streaming
         path=(
             "paracrawl-release1.en-{src}.zipporah0-dedup-clean.{src}",
             "paracrawl-release1.en-{src}.zipporah0-dedup-clean.en",
@@ -330,7 +330,7 @@ _TRAIN_SUBSETS = [
         name="paracrawl_v1_ru",
         target="en",
         sources={"ru"},
-        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz",
+        url="https://s3.amazonaws.com/web-language-models/paracrawl/release1/paracrawl-release1.en-ru.zipporah0-dedup-clean.tgz",  # TODO(QL): use gzip for streaming
         path=(
             "paracrawl-release1.en-ru.zipporah0-dedup-clean.ru",
             "paracrawl-release1.en-ru.zipporah0-dedup-clean.en",
@@ -357,7 +357,7 @@ _TRAIN_SUBSETS = [
         name="rapid_2016",
         target="en",
         sources={"de", "et", "fi"},
-        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/translation-task/rapid2016.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main-zip/translation-task/rapid2016.zip",
         path=("rapid2016.{0}-{1}.{src}", "rapid2016.{0}-{1}.en"),
     ),
     SubDataset(
@@ -385,21 +385,21 @@ _TRAIN_SUBSETS = [
         name="uncorpus_v1",
         target="en",
         sources={"ru", "zh"},
-        url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main/UNv1.0.en-{src}.tar.gz",
+        url="https://huggingface.co/datasets/wmt/uncorpus/resolve/main-zip/UNv1.0.en-{src}.zip",
         path=("en-{src}/UNv1.0.en-{src}.{src}", "en-{src}/UNv1.0.en-{src}.en"),
     ),
     SubDataset(
         name="wikiheadlines_fi",
         target="en",
         sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/wiki-titles.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
         path="wiki/fi-en/titles.fi-en",
     ),
     SubDataset(
         name="wikiheadlines_hi",
         target="en",
         sources={"hi"},
-        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main/wiki-titles.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt14/resolve/main-zip/wiki-titles.zip",
         path="wiki/hi-en/wiki-titles.hi-en",
     ),
     SubDataset(
@@ -407,7 +407,7 @@ _TRAIN_SUBSETS = [
         name="wikiheadlines_ru",
         target="en",
         sources={"ru"},
-        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main/wiki-titles.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt15/resolve/main-zip/wiki-titles.zip",
         path="wiki/ru-en/wiki.ru-en",
     ),
     SubDataset(
@@ -431,7 +431,7 @@ _TRAIN_SUBSETS = [
         name=ss,
         target="en",
         sources={"zh"},
-        url="ftp://cwmt-wmt:cwmt-wmt@datasets.nju.edu.cn/parallel/%s.zip" % ss,
+        url="https://huggingface.co/datasets/wmt/wmt18/resolve/main/cwmt-wmt/%s.zip" % ss,
         path=("%s/*_c[hn].txt" % ss, "%s/*_en.txt" % ss),
     )
     for ss in CWMT_SUBSET_NAMES
@@ -442,175 +442,175 @@ _DEV_SUBSETS = [
         name="euelections_dev2019",
         target="de",
         sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/euelections_dev2019.fr-de.src.fr", "dev/euelections_dev2019.fr-de.tgt.de"),
     ),
     SubDataset(
         name="newsdev2014",
         target="en",
         sources={"hi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2014.hi", "dev/newsdev2014.en"),
     ),
     SubDataset(
         name="newsdev2015",
         target="en",
         sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2015-fien-src.{src}.sgm", "dev/newsdev2015-fien-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdiscussdev2015",
         target="en",
         sources={"ro", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdev2016",
         target="en",
         sources={"ro", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2016-{src}en-src.{src}.sgm", "dev/newsdev2016-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdev2017",
         target="en",
         sources={"lv", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2017-{src}en-src.{src}.sgm", "dev/newsdev2017-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdev2018",
         target="en",
         sources={"et"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2018-{src}en-src.{src}.sgm", "dev/newsdev2018-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdev2019",
         target="en",
         sources={"gu", "kk", "lt"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdev2019-{src}en-src.{src}.sgm", "dev/newsdev2019-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdiscussdev2015",
         target="en",
         sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdiscussdev2015-{src}en-src.{src}.sgm", "dev/newsdiscussdev2015-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdiscusstest2015",
         target="en",
         sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newssyscomb2009",
         target="en",
         sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newssyscomb2009.{src}", "dev/newssyscomb2009.en"),
     ),
     SubDataset(
         name="newstest2008",
         target="en",
         sources={"cs", "de", "es", "fr", "hu"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/news-test2008.{src}", "dev/news-test2008.en"),
     ),
     SubDataset(
         name="newstest2009",
         target="en",
         sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2009.{src}", "dev/newstest2009.en"),
     ),
     SubDataset(
         name="newstest2010",
         target="en",
         sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2010.{src}", "dev/newstest2010.en"),
     ),
     SubDataset(
         name="newstest2011",
         target="en",
         sources={"cs", "de", "es", "fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2011.{src}", "dev/newstest2011.en"),
     ),
     SubDataset(
         name="newstest2012",
         target="en",
         sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2012.{src}", "dev/newstest2012.en"),
     ),
     SubDataset(
         name="newstest2013",
         target="en",
         sources={"cs", "de", "es", "fr", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2013.{src}", "dev/newstest2013.en"),
     ),
     SubDataset(
         name="newstest2014",
         target="en",
         sources={"cs", "de", "es", "fr", "hi", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2014-{src}en-src.{src}.sgm", "dev/newstest2014-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newstest2015",
         target="en",
         sources={"cs", "de", "fi", "ru"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2015-{src}en-src.{src}.sgm", "dev/newstest2015-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newsdiscusstest2015",
         target="en",
         sources={"fr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newsdiscusstest2015-{src}en-src.{src}.sgm", "dev/newsdiscusstest2015-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newstest2016",
         target="en",
         sources={"cs", "de", "fi", "ro", "ru", "tr"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2016-{src}en-src.{src}.sgm", "dev/newstest2016-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newstestB2016",
         target="en",
         sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstestB2016-enfi-ref.{src}.sgm", "dev/newstestB2016-enfi-src.en.sgm"),
     ),
     SubDataset(
         name="newstest2017",
         target="en",
         sources={"cs", "de", "fi", "lv", "ru", "tr", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2017-{src}en-src.{src}.sgm", "dev/newstest2017-{src}en-ref.en.sgm"),
     ),
     SubDataset(
         name="newstestB2017",
         target="en",
         sources={"fi"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstestB2017-fien-src.fi.sgm", "dev/newstestB2017-fien-ref.en.sgm"),
     ),
     SubDataset(
         name="newstest2018",
         target="en",
         sources={"cs", "de", "et", "fi", "ru", "tr", "zh"},
-        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main/translation-task/dev.tgz",
+        url="https://huggingface.co/datasets/wmt/wmt19/resolve/main-zip/translation-task/dev.zip",
         path=("dev/newstest2018-{src}en-src.{src}.sgm", "dev/newstest2018-{src}en-ref.en.sgm"),
     ),
 ]
@@ -658,9 +658,7 @@ class WmtConfig(datasets.BuilderConfig):
         # TODO(PVP): remove when manual dir works
         # +++++++++++++++++++++
         if language_pair[1] in ["cs", "hi", "ru"]:
-            assert NotImplementedError(
-                "The dataset for {}-en is currently not fully supported.".format(language_pair[1])
-            )
+            assert NotImplementedError(f"The dataset for {language_pair[1]}-en is currently not fully supported.")
         # +++++++++++++++++++++
 
 
@@ -730,7 +728,7 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
             if dataset.get_manual_dl_files(source):
                 # TODO(PVP): following two lines skip configs that are incomplete for now
                 # +++++++++++++++++++++
-                logger.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, self.config.name))
+                logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
                 continue
                 # +++++++++++++++++++++
 
@@ -741,9 +739,7 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
                 ]
                 assert all(
                     os.path.exists(path) for path in manual_paths
-                ), "For {0}, you must manually download the following file(s) from {1} and place them in {2}: {3}".format(
-                    dataset.name, dataset.get_url(source), dl_manager.manual_dir, ", ".join(manual_dl_files)
-                )
+                ), f"For {dataset.name}, you must manually download the following file(s) from {dataset.get_url(source)} and place them in {dl_manager.manual_dir}: {', '.join(manual_dl_files)}"
 
                 # set manual path for correct subset
                 manual_paths_dict[ss_name] = manual_paths
@@ -779,24 +775,36 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
                 for ex_dir, rel_path in zip(extract_dirs, rel_paths)
             ]
 
+        def _get_filenames(dataset):
+            rel_paths = dataset.get_path(source)
+            urls = dataset.get_url(source)
+            if len(urls) == 1:
+                urls = urls * len(rel_paths)
+            return [rel_path if rel_path else os.path.basename(url) for url, rel_path in zip(urls, rel_paths)]
+
         for ss_name in split_subsets:
             # TODO(PVP) remove following five lines when manual data works
             # +++++++++++++++++++++
             dataset = DATASET_MAP[ss_name]
             source, _ = self.config.language_pair
             if dataset.get_manual_dl_files(source):
-                logger.info("Skipping {} for now. Incomplete dataset for {}".format(dataset.name, self.config.name))
+                logger.info(f"Skipping {dataset.name} for now. Incomplete dataset for {self.config.name}")
                 continue
             # +++++++++++++++++++++
 
             logger.info("Generating examples from: %s", ss_name)
+            print("Generating examples from: %s", ss_name)
             dataset = DATASET_MAP[ss_name]
             extract_dirs = extraction_map[ss_name]
             files = _get_local_paths(dataset, extract_dirs)
+            filenames = _get_filenames(dataset)
+
+            sub_generator_args = tuple(files)
 
             if ss_name.startswith("czeng"):
                 if ss_name.endswith("16pre"):
                     sub_generator = functools.partial(_parse_tsv, language_pair=("en", "cs"))
+                    sub_generator_args += tuple(filenames)
                 elif ss_name.endswith("17"):
                     filter_path = _get_local_paths(_CZENG17_FILTER, extraction_map[_CZENG17_FILTER.name])[0]
                     sub_generator = functools.partial(_parse_czeng, filter_path=filter_path)
@@ -809,18 +817,21 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
                     sub_generator = _parse_frde_bitext
                 else:
                     sub_generator = _parse_parallel_sentences
+                    sub_generator_args += tuple(filenames)
             elif len(files) == 1:
-                fname = files[0]
+                fname = filenames[0]
                 # Note: Due to formatting used by `download_manager`, the file
                 # extension may not be at the end of the file path.
                 if ".tsv" in fname:
                     sub_generator = _parse_tsv
+                    sub_generator_args += tuple(filenames)
                 elif (
                     ss_name.startswith("newscommentary_v14")
                     or ss_name.startswith("europarl_v9")
                     or ss_name.startswith("wikititles_v1")
                 ):
                     sub_generator = functools.partial(_parse_tsv, language_pair=self.config.language_pair)
+                    sub_generator_args += tuple(filenames)
                 elif "tmx" in fname or ss_name.startswith("paracrawl_v3"):
                     sub_generator = _parse_tmx
                 elif ss_name.startswith("wikiheadlines"):
@@ -830,28 +841,33 @@ class Wmt(ABC, datasets.GeneratorBasedBuilder):
             else:
                 raise ValueError("Invalid number of files: %d" % len(files))
 
-            for sub_key, ex in sub_generator(*files):
+            for sub_key, ex in sub_generator(*sub_generator_args):
                 if not all(ex.values()):
                     continue
                 # TODO(adarob): Add subset feature.
                 # ex["subset"] = subset
-                key = "{}/{}".format(ss_name, sub_key)
+                key = f"{ss_name}/{sub_key}"
                 if with_translation is True:
                     ex = {"translation": ex}
                 yield key, ex
 
 
-def _parse_parallel_sentences(f1, f2):
+def _parse_parallel_sentences(f1, f2, filename1, filename2):
     """Returns examples from parallel SGML or text files, which may be gzipped."""
 
-    def _parse_text(path):
+    def _parse_text(path, original_filename):
         """Returns the sentences from a single text file, which may be gzipped."""
-        split_path = path.split(".")
+        split_path = original_filename.split(".")
 
         if split_path[-1] == "gz":
             lang = split_path[-2]
-            with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
-                return g.read().decode("utf-8").split("\n"), lang
+
+            def gen():
+                with open(path, "rb") as f, gzip.GzipFile(fileobj=f) as g:
+                    for line in g:
+                        yield line.decode("utf-8").rstrip()
+
+            return gen(), lang
 
         if split_path[-1] == "txt":
             # CWMT
@@ -859,25 +875,32 @@ def _parse_parallel_sentences(f1, f2):
             lang = "zh" if lang in ("ch", "cn") else lang
         else:
             lang = split_path[-1]
-        with open(path, "rb") as f:
-            return f.read().decode("utf-8").split("\n"), lang
 
-    def _parse_sgm(path):
+        def gen():
+            with open(path, "rb") as f:
+                for line in f:
+                    yield line.decode("utf-8").rstrip()
+
+        return gen(), lang
+
+    def _parse_sgm(path, original_filename):
         """Returns sentences from a single SGML file."""
-        lang = path.split(".")[-2]
-        sentences = []
+        lang = original_filename.split(".")[-2]
         # Note: We can't use the XML parser since some of the files are badly
         # formatted.
         seg_re = re.compile(r"<seg id=\"\d+\">(.*)</seg>")
-        with open(path, encoding="utf-8") as f:
-            for line in f:
-                seg_match = re.match(seg_re, line)
-                if seg_match:
-                    assert len(seg_match.groups()) == 1
-                    sentences.append(seg_match.groups()[0])
-        return sentences, lang
 
-    parse_file = _parse_sgm if f1.endswith(".sgm") else _parse_text
+        def gen():
+            with open(path, encoding="utf-8") as f:
+                for line in f:
+                    seg_match = re.match(seg_re, line)
+                    if seg_match:
+                        assert len(seg_match.groups()) == 1
+                        yield seg_match.groups()[0]
+
+        return gen(), lang
+
+    parse_file = _parse_sgm if os.path.basename(f1).endswith(".sgm") else _parse_text
 
     # Some datasets (e.g., CWMT) contain multiple parallel files specified with
     # a wildcard. We sort both sets to align them and parse them one by one.
@@ -893,34 +916,19 @@ def _parse_parallel_sentences(f1, f2):
     )
 
     for f_id, (f1_i, f2_i) in enumerate(zip(sorted(f1_files), sorted(f2_files))):
-        l1_sentences, l1 = parse_file(f1_i)
-        l2_sentences, l2 = parse_file(f2_i)
-
-        assert len(l1_sentences) == len(l2_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
-            len(l1_sentences),
-            len(l2_sentences),
-            f1_i,
-            f2_i,
-        )
+        l1_sentences, l1 = parse_file(f1_i, filename1)
+        l2_sentences, l2 = parse_file(f2_i, filename2)
 
         for line_id, (s1, s2) in enumerate(zip(l1_sentences, l2_sentences)):
-            key = "{}/{}".format(f_id, line_id)
+            key = f"{f_id}/{line_id}"
             yield key, {l1: s1, l2: s2}
 
 
 def _parse_frde_bitext(fr_path, de_path):
-    with open(fr_path, encoding="utf-8") as f:
-        fr_sentences = f.read().split("\n")
-    with open(de_path, encoding="utf-8") as f:
-        de_sentences = f.read().split("\n")
-    assert len(fr_sentences) == len(de_sentences), "Sizes do not match: %d vs %d for %s vs %s." % (
-        len(fr_sentences),
-        len(de_sentences),
-        fr_path,
-        de_path,
-    )
-    for line_id, (s1, s2) in enumerate(zip(fr_sentences, de_sentences)):
-        yield line_id, {"fr": s1, "de": s2}
+    with open(fr_path, encoding="utf-8") as fr_f:
+        with open(de_path, encoding="utf-8") as de_f:
+            for line_id, (s1, s2) in enumerate(zip(fr_f, de_f)):
+                yield line_id, {"fr": s1.rstrip(), "de": s2.rstrip()}
 
 
 def _parse_tmx(path):
@@ -946,11 +954,11 @@ def _parse_tmx(path):
                 elem.clear()
 
 
-def _parse_tsv(path, language_pair=None):
+def _parse_tsv(path, filename, language_pair=None):
     """Generates examples from TSV file."""
     if language_pair is None:
-        lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])\.tsv", path)
-        assert lang_match is not None, "Invalid TSV filename: %s" % path
+        lang_match = re.match(r".*\.([a-z][a-z])-([a-z][a-z])\.tsv", filename)
+        assert lang_match is not None, "Invalid TSV filename: %s" % filename
         l1, l2 = lang_match.groups()
     else:
         l1, l2 = language_pair
@@ -997,7 +1005,7 @@ def _parse_czeng(*paths, **kwargs):
                         block_match = re.match(re_block, id_)
                         if block_match and block_match.groups()[0] in bad_blocks:
                             continue
-                    sub_key = "{}/{}".format(filename, line_id)
+                    sub_key = f"{filename}/{line_id}"
                     yield sub_key, {
                         "cs": cs.strip(),
                         "en": en.strip(),