Datasets:
wili_2018

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

README.md ADDED Viewed

	@@ -0,0 +1,387 @@

+---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+languages:
+- af
+- am
+- an
+- as
+- av
+- ay
+- bs
+- ce
+- co
+- cv
+- dv
+- eo
+- gl
+- gn
+- gu
+- ha
+- hr
+- ht
+- ia
+- id
+- ie
+- ig
+- io
+- ja
+- jv
+- km
+- ko
+- ku
+- kv
+- ky
+- lb
+- lg
+- li
+- ln
+- lo
+- mg
+- mi
+- ml
+- mn
+- mr
+- ms
+- my
+- ne
+- om
+- or
+- os
+- pa
+- rm
+- rw
+- sc
+- sd
+- si
+- sk
+- sn
+- so
+- sr
+- su
+- sw
+- ta
+- th
+- tl
+- tn
+- to
+- ug
+- vi
+- vo
+- wa
+- wo
+- xh
+- yo
+- zh
+- ar
+- az
+- ba
+- be
+- bg
+- bn
+- bo
+- br
+- ca
+- cs
+- cy
+- da
+- de
+- el
+- en
+- es
+- et
+- eu
+- fa
+- fi
+- fo
+- fr
+- fy
+- ga
+- gd
+- gv
+- he
+- hi
+- hu
+- hy
+- is
+- it
+- ka
+- kk
+- kn
+- kw
+- la
+- lt
+- lv
+- mk
+- mt
+- nb
+- nl
+- nn
+- nv
+- oc
+- pl
+- ps
+- pt
+- qu
+- ro
+- ru
+- sa
+- sh
+- sl
+- sq
+- sv
+- te
+- tg
+- tk
+- tr
+- tt
+- uk
+- ur
+- uz
+- yi
+- ace
+- als
+- ang
+- arz
+- ast
+- azb
+- bar
+- bcl
+- bho
+- bjn
+- bpy
+- bxr
+- cbk
+- cdo
+- ceb
+- chr
+- ckb
+- crh
+- csb
+- diq
+- dsb
+- dty
+- egl
+- ext
+- frp
+- fur
+- gag
+- glk
+- hak
+- hif
+- hsb
+- ilo
+- jam
+- jbo
+- kaa
+- kab
+- kbd
+- koi
+- kok
+- krc
+- ksh
+- lad
+- lez
+- lij
+- lmo
+- lrc
+- ltg
+- lzh
+- mai
+- mdf
+- mhr
+- min
+- mrj
+- mwl
+- myv
+- mzn
+- nan
+- nap
+- nci
+- nds
+- new
+- nrm
+- nso
+- olo
+- pag
+- pam
+- pap
+- pcd
+- pdc
+- pfl
+- pnb
+- rue
+- rup
+- sah
+- scn
+- sco
+- sgs
+- sme
+- srn
+- stq
+- szl
+- tcy
+- tet
+- tyv
+- udm
+- vec
+- vep
+- vls
+- vro
+- war
+- wuu
+- xmf
+- zea
+- other-roa-tara
+- other-zh-yue
+- other-map-bms
+- other-nds-nl
+- other-be-tarask
+licenses:
+- odbl-1-0
+multilinguality:
+- multilingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- text-classification-other-language-identification
+---
+# Dataset Card for wili_2018
+## 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:** https://zenodo.org/record/841984
+- **Repository:** [Needs More Information]
+- **Paper:** https://arxiv.org/pdf/1801.07779
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** Thoma, Martin (Email: info@martin-thoma.de)
+### Dataset Summary
+WiLI-2018, the Wikipedia language identification benchmark dataset, contains 235000 paragraphs of 235 languages. The dataset is balanced and a train-test split is provided.
+### Supported Tasks and Leaderboards
+[Needs More Information]
+### Languages
+235 Different Languages
+## Dataset Structure
+### Data Instances
+```
+{
+    'label': 207,
+    'sentence': 'Ti Turkia ket maysa a demokrata, sekular, unitario, batay-linteg a republika nga addaan ti taga-ugma a tinawtawid a kultura. Ti Turkia ket umadadu a naipatipon iti Laud babaen ti panagkameng kadagiti organisasion a kas ti Konsilo iti Europa, NATO, OECD, OSCE ken ti G-20 a dagiti kangrunaan nga ekonomia. Ti Turkia ket nangrugi a nakitulag ti napno a panagkameng iti Kappon ti Europa idi 2005, nga isu ket maysa idin a kumaduaan a kameng iti Europeano a Komunidad ti Ekonomia manipud idi 1963 ken nakadanon ti maysa a tulagan ti kappon ti aduana idi 1995. Ti Turkia ket nagtaraken iti asideg a kultural, politikal, ekonomiko ken industria a panakibiang iti Tengnga a Daya, dagiti Turko nga estado iti Tengnga nga Asia ken dagiti pagilian ti Aprika babaen ti panagkameng kadagiti organisasion a kas ti Turko a Konsilo, Nagsaupan nga Administrasion iti Turko nga Arte ken Kultura, Organisasion iti Islamiko a Panagtitinnulong ken ti Organisasion ti Ekonomiko a Panagtitinnulong.'
+}
+```
+### Data Fields
+[Needs More Information]
+### Data Splits
+175000 lines of text each for train and test data.
+## Dataset Creation
+### Curation Rationale
+[Needs More Information]
+### Source Data
+#### Initial Data Collection and Normalization
+[Needs More Information]
+#### Who are the source language producers?
+[Needs More Information]
+### Annotations
+#### Annotation process
+[Needs More Information]
+#### Who are the annotators?
+[Needs More Information]
+### Personal and Sensitive Information
+[Needs More Information]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[Needs More Information]
+### Discussion of Biases
+[Needs More Information]
+### Other Known Limitations
+[Needs More Information]
+## Additional Information
+### Dataset Curators
+The dataset was initially created by Thomas Martin
+### Licensing Information
+ODC Open Database License v1.0
+### Citation Information
+```
+@dataset{thoma_martin_2018_841984,
+  author       = {Thoma, Martin},
+  title        = {{WiLI-2018 - Wikipedia Language Identification database}},
+  month        = jan,
+  year         = 2018,
+  publisher    = {Zenodo},
+  version      = {1.0.0},
+  doi          = {10.5281/zenodo.841984},
+  url          = {https://doi.org/10.5281/zenodo.841984}
+}
+```

dataset_infos.json ADDED Viewed

	@@ -0,0 +1 @@

+ {"WiLI-2018 dataset": {"description": "It is a benchmark dataset for language identification and contains 235000 paragraphs of 235 languages\n", "citation": "@dataset{thoma_martin_2018_841984,\n author = {Thoma, Martin},\n title = {{WiLI-2018 - Wikipedia Language Identification database}},\n month = jan,\n year = 2018,\n publisher = {Zenodo},\n version = {1.0.0},\n doi = {10.5281/zenodo.841984},\n url = {https://doi.org/10.5281/zenodo.841984}\n}\n", "homepage": "https://zenodo.org/record/841984", "license": "ODC Open Database License v1.0", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 235, "names": ["cdo", "glk", "jam", "lug", "san", "rue", "wol", "new", "mwl", "bre", "ara", "hye", "xmf", "ext", "cor", "yor", "div", "asm", "lat", "cym", "hif", "ace", "kbd", "tgk", "rus", "nso", "mya", "msa", "ava", "cbk", "urd", "deu", "swa", "pus", "bxr", "udm", "csb", "yid", "vro", "por", "pdc", "eng", "tha", "hat", "lmo", "pag", "jav", "chv", "nan", "sco", "kat", "bho", "bos", "kok", "oss", "mri", "fry", "cat", "azb", "kin", "hin", "sna", "dan", "egl", "mkd", "ron", "bul", "hrv", "som", "pam", "nav", "ksh", "nci", "khm", "sgs", "srn", "bar", "cos", "ckb", "pfl", "arz", "roa-tara", "fra", "mai", "zh-yue", "guj", "fin", "kir", "vol", "hau", "afr", "uig", "lao", "swe", "slv", "kor", "szl", "srp", "dty", "nrm", "dsb", "ind", "wln", "pnb", "ukr", "bpy", "vie", "tur", "aym", "lit", "zea", "pol", "est", "scn", "vls", "stq", "gag", "grn", "kaz", "ben", "pcd", "bjn", "krc", "amh", "diq", "ltz", "ita", "kab", "bel", "ang", "mhr", "che", "koi", "glv", "ido", "fao", "bak", "isl", "bcl", "tet", "jpn", "kur", "map-bms", "tyv", "olo", "arg", "ori", "lim", "tel", "lin", "roh", "sqi", "xho", "mlg", "fas", "hbs", "tam", "aze", "lad", "nob", "sin", "gla", "nap", "snd", "ast", "mal", "mdf", "tsn", "nds", "tgl", "nno", "sun", "lzh", "jbo", "crh", "pap", "oci", "hak", "uzb", "zho", "hsb", "sme", "mlt", "vep", "lez", "nld", "nds-nl", "mrj", "spa", "ceb", "ina", "heb", "hun", "que", "kaa", "mar", "vec", "frp", "ell", "sah", "eus", "ces", "slk", "chr", "lij", "nep", "srd", "ilo", "be-tarask", "bod", "orm", "war", "glg", "mon", "gle", "min", "ibo", "ile", "epo", "lav", "lrc", "als", "mzn", "rup", "fur", "tat", "myv", "pan", "ton", "kom", "wuu", "tcy", "tuk", "kan", "ltg"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "wili_2018", "config_name": "WiLI-2018 dataset", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 65408201, "num_examples": 117500, "dataset_name": "wili_2018"}, "test": {"name": "test", "num_bytes": 66491260, "num_examples": 117500, "dataset_name": "wili_2018"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1ZzlIQvw1KNBG97QQCfdatvVrrbeLaM1u": {"num_bytes": 64716393, "checksum": "895b3892a1edba1702b0f2117b756204ccc177a1c285420234bdb5d717ad4100"}, "https://drive.google.com/uc?export=download&id=1Xx4kFc1Xdzz8AhDasxZ0cSa-a35EQSDZ": {"num_bytes": 65799958, "checksum": "663f32b6f7d8a26b83e251803d386f29dcd558762125f4f8289f2cef067d4ce8"}}, "download_size": 130516351, "post_processing_size": null, "dataset_size": 131899461, "size_in_bytes": 262415812}}

dummy/WiLI-2018 dataset/1.1.0/dummy_data.zip ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:9e870a8d86efe03d0497f8d3fe1f4adee41d50b042bc82b1de4c158d5221d369
+size 4225

wili_2018.py ADDED Viewed

	@@ -0,0 +1,333 @@

+# 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.
+"""WiLI-2018, the Wikipedia language identification benchmark dataset"""
+from __future__ import absolute_import, division, print_function
+import datasets
+_CITATION = """\
+@dataset{thoma_martin_2018_841984,
+  author       = {Thoma, Martin},
+  title        = {{WiLI-2018 - Wikipedia Language Identification database}},
+  month        = jan,
+  year         = 2018,
+  publisher    = {Zenodo},
+  version      = {1.0.0},
+  doi          = {10.5281/zenodo.841984},
+  url          = {https://doi.org/10.5281/zenodo.841984}
+}
+"""
+_DESCRIPTION = """\
+It is a benchmark dataset for language identification and contains 235000 paragraphs of 235 languages
+"""
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://zenodo.org/record/841984"
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = "ODC Open Database License v1.0"
+# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
+_TRAIN_DOWNLOAD_URL = "https://drive.google.com/uc?export=download&id=1ZzlIQvw1KNBG97QQCfdatvVrrbeLaM1u"
+_TEST_DOWNLOAD_URL = "https://drive.google.com/uc?export=download&id=1Xx4kFc1Xdzz8AhDasxZ0cSa-a35EQSDZ"
+_CLASSES = [
+    "cdo",
+    "glk",
+    "jam",
+    "lug",
+    "san",
+    "rue",
+    "wol",
+    "new",
+    "mwl",
+    "bre",
+    "ara",
+    "hye",
+    "xmf",
+    "ext",
+    "cor",
+    "yor",
+    "div",
+    "asm",
+    "lat",
+    "cym",
+    "hif",
+    "ace",
+    "kbd",
+    "tgk",
+    "rus",
+    "nso",
+    "mya",
+    "msa",
+    "ava",
+    "cbk",
+    "urd",
+    "deu",
+    "swa",
+    "pus",
+    "bxr",
+    "udm",
+    "csb",
+    "yid",
+    "vro",
+    "por",
+    "pdc",
+    "eng",
+    "tha",
+    "hat",
+    "lmo",
+    "pag",
+    "jav",
+    "chv",
+    "nan",
+    "sco",
+    "kat",
+    "bho",
+    "bos",
+    "kok",
+    "oss",
+    "mri",
+    "fry",
+    "cat",
+    "azb",
+    "kin",
+    "hin",
+    "sna",
+    "dan",
+    "egl",
+    "mkd",
+    "ron",
+    "bul",
+    "hrv",
+    "som",
+    "pam",
+    "nav",
+    "ksh",
+    "nci",
+    "khm",
+    "sgs",
+    "srn",
+    "bar",
+    "cos",
+    "ckb",
+    "pfl",
+    "arz",
+    "roa-tara",
+    "fra",
+    "mai",
+    "zh-yue",
+    "guj",
+    "fin",
+    "kir",
+    "vol",
+    "hau",
+    "afr",
+    "uig",
+    "lao",
+    "swe",
+    "slv",
+    "kor",
+    "szl",
+    "srp",
+    "dty",
+    "nrm",
+    "dsb",
+    "ind",
+    "wln",
+    "pnb",
+    "ukr",
+    "bpy",
+    "vie",
+    "tur",
+    "aym",
+    "lit",
+    "zea",
+    "pol",
+    "est",
+    "scn",
+    "vls",
+    "stq",
+    "gag",
+    "grn",
+    "kaz",
+    "ben",
+    "pcd",
+    "bjn",
+    "krc",
+    "amh",
+    "diq",
+    "ltz",
+    "ita",
+    "kab",
+    "bel",
+    "ang",
+    "mhr",
+    "che",
+    "koi",
+    "glv",
+    "ido",
+    "fao",
+    "bak",
+    "isl",
+    "bcl",
+    "tet",
+    "jpn",
+    "kur",
+    "map-bms",
+    "tyv",
+    "olo",
+    "arg",
+    "ori",
+    "lim",
+    "tel",
+    "lin",
+    "roh",
+    "sqi",
+    "xho",
+    "mlg",
+    "fas",
+    "hbs",
+    "tam",
+    "aze",
+    "lad",
+    "nob",
+    "sin",
+    "gla",
+    "nap",
+    "snd",
+    "ast",
+    "mal",
+    "mdf",
+    "tsn",
+    "nds",
+    "tgl",
+    "nno",
+    "sun",
+    "lzh",
+    "jbo",
+    "crh",
+    "pap",
+    "oci",
+    "hak",
+    "uzb",
+    "zho",
+    "hsb",
+    "sme",
+    "mlt",
+    "vep",
+    "lez",
+    "nld",
+    "nds-nl",
+    "mrj",
+    "spa",
+    "ceb",
+    "ina",
+    "heb",
+    "hun",
+    "que",
+    "kaa",
+    "mar",
+    "vec",
+    "frp",
+    "ell",
+    "sah",
+    "eus",
+    "ces",
+    "slk",
+    "chr",
+    "lij",
+    "nep",
+    "srd",
+    "ilo",
+    "be-tarask",
+    "bod",
+    "orm",
+    "war",
+    "glg",
+    "mon",
+    "gle",
+    "min",
+    "ibo",
+    "ile",
+    "epo",
+    "lav",
+    "lrc",
+    "als",
+    "mzn",
+    "rup",
+    "fur",
+    "tat",
+    "myv",
+    "pan",
+    "ton",
+    "kom",
+    "wuu",
+    "tcy",
+    "tuk",
+    "kan",
+    "ltg",
+]
+class Wili_2018(datasets.GeneratorBasedBuilder):
+    """WiLI Language Identification Dataset"""
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="WiLI-2018 dataset",
+            version=VERSION,
+            description="Plain text of import of WiLI-2018",
+        )
+    ]
+    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(
+                {"sentence": datasets.Value("string"), "label": datasets.features.ClassLabel(names=_CLASSES)}
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+    def _split_generators(self, dl_manager):
+        train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
+        test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
+        ]
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for id_, line in enumerate(f):
+                text, label = line.rsplit(",", 1)
+                text = text.strip('"')
+                label = int(label.strip())
+                yield id_, {"sentence": text, "label": label - 1}