diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..957b2579c6ef20995a09efd9a17f8fd90606f5ed
--- /dev/null
+++ b/.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
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
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index 0000000000000000000000000000000000000000..ebeee911131d147325c2aa66050fb7d342701f99
--- /dev/null
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@@ -0,0 +1,605 @@
+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+  ady:
+  - ady
+  ang:
+  - ang
+  ara:
+  - ar
+  arn:
+  - arn
+  ast:
+  - ast
+  aze:
+  - az
+  bak:
+  - ba
+  bel:
+  - be
+  ben:
+  - bn
+  bod:
+  - bo
+  bre:
+  - br
+  bul:
+  - bg
+  cat:
+  - ca
+  ces:
+  - cs
+  chu:
+  - cu
+  ckb:
+  - ckb
+  cor:
+  - kw
+  crh:
+  - crh
+  csb:
+  - csb
+  cym:
+  - cy
+  dan:
+  - da
+  deu:
+  - de
+  dsb:
+  - dsb
+  ell:
+  - el
+  eng:
+  - en
+  est:
+  - et
+  eus:
+  - eu
+  fao:
+  - fo
+  fas:
+  - fa
+  fin:
+  - fi
+  fra:
+  - fr
+  frm:
+  - frm
+  fro:
+  - fro
+  frr:
+  - frr
+  fry:
+  - fy
+  fur:
+  - fur
+  gal:
+  - gal
+  gla:
+  - gd
+  gle:
+  - ga
+  glv:
+  - gv
+  gmh:
+  - gmh
+  gml:
+  - gml
+  got:
+  - got
+  grc:
+  - grc
+  hai:
+  - hai
+  hbs:
+  - sh
+  heb:
+  - he
+  hin:
+  - hi
+  hun:
+  - hu
+  hye:
+  - hy
+  isl:
+  - is
+  ita:
+  - it
+  izh:
+  - izh
+  kal:
+  - kl
+  kan:
+  - kn
+  kat:
+  - ka
+  kaz:
+  - kk
+  kbd:
+  - kbd
+  kjh:
+  - kjh
+  klr:
+  - klr
+  kmr:
+  - kmr
+  krl:
+  - krl
+  lat:
+  - la
+  lav:
+  - lv
+  lit:
+  - lt
+  liv:
+  - liv
+  lld:
+  - lld
+  lud:
+  - lud
+  mkd:
+  - mk
+  mlt:
+  - mt
+  mwf:
+  - mwf
+  nap:
+  - nap
+  nav:
+  - nv
+  nds:
+  - nds
+  nld:
+  - nl
+  nno:
+  - nn
+  nob:
+  - nb
+  oci:
+  - oc
+  olo:
+  - olo
+  osx:
+  - osx
+  pol:
+  - pl
+  por:
+  - pt
+  pus:
+  - ps
+  que:
+  - qu
+  ron:
+  - ro
+  rus:
+  - ru
+  san:
+  - sa
+  sga:
+  - sga
+  slv:
+  - sl
+  sme:
+  - sme
+  spa:
+  - es
+  sqi:
+  - sq
+  swc:
+  - swc
+  swe:
+  - sv
+  syc:
+  - syc
+  tat:
+  - tt
+  tel:
+  - te
+  tgk:
+  - tg
+  tuk:
+  - tk
+  tur:
+  - tr
+  ukr:
+  - uk
+  urd:
+  - ur
+  uzb:
+  - uz
+  vec:
+  - vec
+  vep:
+  - vep
+  vot:
+  - vot
+  xcl:
+  - xcl
+  xno:
+  - xno
+  yid:
+  - yi
+  zul:
+  - zu
+licenses:
+- cc-by-sa-3-0
+multilinguality:
+- monolingual
+size_categories:
+  ady:
+  - 1K<n<10K
+  ang:
+  - 1K<n<10K
+  ara:
+  - 1K<n<10K
+  arn:
+  - n<1K
+  ast:
+  - n<1K
+  aze:
+  - n<1K
+  bak:
+  - 1K<n<10K
+  bel:
+  - 1K<n<10K
+  ben:
+  - n<1K
+  bod:
+  - 1K<n<10K
+  bre:
+  - n<1K
+  bul:
+  - 1K<n<10K
+  cat:
+  - 1K<n<10K
+  ces:
+  - 1K<n<10K
+  chu:
+  - n<1K
+  ckb:
+  - n<1K
+  cor:
+  - n<1K
+  crh:
+  - 1K<n<10K
+  csb:
+  - n<1K
+  cym:
+  - n<1K
+  dan:
+  - 1K<n<10K
+  deu:
+  - 10K<n<100K
+  dsb:
+  - 1K<n<10K
+  ell:
+  - 10K<n<100K
+  eng:
+  - 10K<n<100K
+  est:
+  - n<1K
+  eus:
+  - n<1K
+  fao:
+  - 1K<n<10K
+  fas:
+  - n<1K
+  fin:
+  - 10K<n<100K
+  fra:
+  - 10K<n<100K
+  frm:
+  - n<1K
+  fro:
+  - 1K<n<10K
+  frr:
+  - n<1K
+  fry:
+  - n<1K
+  fur:
+  - n<1K
+  gal:
+  - n<1K
+  gla:
+  - n<1K
+  gle:
+  - 1K<n<10K
+  glv:
+  - n<1K
+  gmh:
+  - n<1K
+  gml:
+  - n<1K
+  got:
+  - n<1K
+  grc:
+  - 1K<n<10K
+  hai:
+  - n<1K
+  hbs:
+  - 10K<n<100K
+  heb:
+  - n<1K
+  hin:
+  - n<1K
+  hun:
+  - 10K<n<100K
+  hye:
+  - 1K<n<10K
+  isl:
+  - 1K<n<10K
+  ita:
+  - 10K<n<100K
+  izh:
+  - n<1K
+  kal:
+  - n<1K
+  kan:
+  - n<1K
+  kat:
+  - 1K<n<10K
+  kaz:
+  - n<1K
+  kbd:
+  - n<1K
+  kjh:
+  - n<1K
+  klr:
+  - 10K<n<100K
+  kmr:
+  - 10K<n<100K
+  krl:
+  - n<1K
+  lat:
+  - 10K<n<100K
+  lav:
+  - 10K<n<100K
+  lit:
+  - 1K<n<10K
+  liv:
+  - n<1K
+  lld:
+  - n<1K
+  lud:
+  - n<1K
+  mkd:
+  - 10K<n<100K
+  mlt:
+  - n<1K
+  mwf:
+  - n<1K
+  nap:
+  - n<1K
+  nav:
+  - 1K<n<10K
+  nds:
+  - n<1K
+  nld:
+  - 1K<n<10K
+  nno:
+  - 1K<n<10K
+  nob:
+  - 1K<n<10K
+  oci:
+  - n<1K
+  olo:
+  - 10K<n<100K
+  osx:
+  - n<1K
+  pol:
+  - 10K<n<100K
+  por:
+  - 1K<n<10K
+  pus:
+  - n<1K
+  que:
+  - 1K<n<10K
+  ron:
+  - 1K<n<10K
+  rus:
+  - 10K<n<100K
+  san:
+  - n<1K
+  sga:
+  - n<1K
+  slv:
+  - 1K<n<10K
+  sme:
+  - 1K<n<10K
+  spa:
+  - 1K<n<10K
+  sqi:
+  - n<1K
+  swc:
+  - n<1K
+  swe:
+  - 10K<n<100K
+  syc:
+  - n<1K
+  tat:
+  - 1K<n<10K
+  tel:
+  - n<1K
+  tgk:
+  - n<1K
+  tuk:
+  - n<1K
+  tur:
+  - 1K<n<10K
+  ukr:
+  - 1K<n<10K
+  urd:
+  - n<1K
+  uzb:
+  - n<1K
+  vec:
+  - n<1K
+  vep:
+  - 1K<n<10K
+  vot:
+  - n<1K
+  xcl:
+  - 1K<n<10K
+  xno:
+  - n<1K
+  yid:
+  - n<1K
+  zul:
+  - n<1K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+- text-classification
+task_ids:
+- multi-class-classification
+- multi-label-classification
+- structure-prediction-other-morphology
+---
+
+# Dataset Card for [Dataset Name]
+
+## 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)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [UniMorph Homepage](https://unimorph.github.io/)
+- **Repository:** [List of UniMorph repositories](https://github.com/unimorph)
+- **Paper:** [The Composition and Use of the Universal Morphological Feature Schema (UniMorph Schema)](https://unimorph.github.io/doc/unimorph-schema.pdf)
+- **Point of Contact:** [Arya McCarthy](mailto:arya@jhu.edu)
+
+### Dataset Summary
+
+The Universal Morphology (UniMorph) project is a collaborative effort to improve how NLP handles complex morphology in the world’s languages.
+The goal of UniMorph is to annotate morphological data in a universal schema that allows an inflected word from any language to be defined by its lexical meaning,
+typically carried by the lemma, and by a rendering of its inflectional form in terms of a bundle of morphological features from our schema.
+The specification of the schema is described in Sylak-Glassman (2016).
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+The current version of the UniMorph dataset covers 110 languages.
+
+## Dataset Structure
+
+### Data Instances
+
+Each data instance comprises of a lemma and a set of possible realizations with morphological and meaning annotations. For example:
+```
+{'forms': {'Aktionsart': [[], [], [], [], []],
+  'Animacy': [[], [], [], [], []],
+  ...
+  'Finiteness': [[], [], [], [1], []],
+  ...
+  'Number': [[], [], [0], [], []],
+  'Other': [[], [], [], [], []],
+  'Part_Of_Speech': [[7], [10], [7], [7], [10]],
+  ...
+  'Tense': [[1], [1], [0], [], [0]],
+  ...
+  'word': ['ablated', 'ablated', 'ablates', 'ablate', 'ablating']},
+ 'lemma': 'ablate'}
+```
+
+### Data Fields
+
+Each instance in the dataset has the following fields:
+- `lemma`: the common lemma for all all_forms
+- `forms`: all annotated forms for this lemma, with:
+  - `word`: the full word form
+  - [`category`]: a categorical variable denoting one or several tags in a category (several to represent composite tags, originally denoted with `A+B`). The full list of categories and possible tags for each can be found [here](https://github.com/unimorph/unimorph.github.io/blob/master/unimorph-schema-json/dimensions-to-features.json)
+
+
+### Data Splits
+
+[More Information Needed]
+
+## 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
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@yjernite](https://github.com/yjernite) for adding this dataset.
\ No newline at end of file
diff --git a/dataset_infos.json b/dataset_infos.json
new file mode 100644
index 0000000000000000000000000000000000000000..094ea74756eb4aacc0ee962ef4c87658cf889800
--- /dev/null
+++ b/dataset_infos.json
@@ -0,0 +1 @@
+{"ady": {"description": "The Universal Morphology (UniMorph) project is a collaborative effort to improve how NLP handles complex morphology in the world\u2019s languages.\nThe goal of UniMorph is to annotate morphological data in a universal schema that allows an inflected word from any language to be defined by its lexical meaning,\ntypically carried by the lemma, and by a rendering of its inflectional form in terms of a bundle of morphological features from our schema.\nThe specification of the schema is described in Sylak-Glassman (2016).\n", "citation": "@article{sylak2016composition,\n  title={The composition and use of the universal morphological feature schema (unimorph schema)},\n  author={Sylak-Glassman, John},\n  journal={Johns Hopkins University},\n  year={2016}\n}\n", "homepage": "https://unimorph.github.io/", "license": "CC-BY-SA-3.0", "features": {"lemma": {"dtype": "string", "id": null, "_type": "Value"}, "forms": {"feature": {"word": {"dtype": "string", "id": null, "_type": "Value"}, "Aktionsart": {"feature": {"num_classes": 10, "names": ["STAT", "DYN", "TEL", "ATEL", "PCT", "DUR", "ACH", "ACCMP", "SEMEL", "ACTY"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Animacy": {"feature": {"num_classes": 4, "names": ["ANIM", "INAN", "HUM", "NHUM"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Argument_Marking": {"feature": {"num_classes": 36, "names": ["ARGNO1S", "ARGNO2S", "ARGNO3S", "ARGNO1P", "ARGNO2P", "ARGNO3P", "ARGAC1S", "ARGAC2S", "ARGAC3S", "ARGAC1P", "ARGAC2P", "ARGAC3P", "ARGAB1S", "ARGAB2S", "ARGAB3S", "ARGAB1P", "ARGAB2P", "ARGAB3P", "ARGER1S", "ARGER2S", "ARGER3S", "ARGER1P", "ARGER2P", "ARGER3P", "ARGDA1S", "ARGDA2S", "ARGDA3S", "ARGDA1P", "ARGDA2P", "ARGDA3P", "ARGBE1S", "ARGBE2S", "ARGBE3S", "ARGBE1P", "ARGBE2P", "ARGBE3P"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Aspect": {"feature": {"num_classes": 7, "names": ["IPFV", "PFV", "PRF", "PROG", "PROSP", "ITER", "HAB"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Case": {"feature": {"num_classes": 40, "names": ["NOM", "ACC", "ERG", "ABS", "NOMS", "DAT", "BEN", "PRP", "GEN", "REL", "PRT", "INS", "COM", "VOC", "COMPV", "EQTV", "PRIV", "PROPR", "AVR", "FRML", "TRANS", "BYWAY", "INTER", "AT", "POST", "IN", "CIRC", "ANTE", "APUD", "ON", "ONHR", "ONVR", "SUB", "REM", "PROXM", "ESS", "ALL", "ABL", "APPRX", "TERM"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Comparison": {"feature": {"num_classes": 5, "names": ["CMPR", "SPRL", "AB", "RL", "EQT"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Definiteness": {"feature": {"num_classes": 4, "names": ["DEF", "INDF", "SPEC", "NSPEC"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Deixis": {"feature": {"num_classes": 12, "names": ["PROX", "MED", "REMT", "REF1", "REF2", "NOREF", "PHOR", "VIS", "NVIS", "ABV", "EVEN", "BEL"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Evidentiality": {"feature": {"num_classes": 12, "names": ["FH", "DRCT", "SEN", "VISU", "NVSEN", "AUD", "NFH", "QUOT", "RPRT", "HRSY", "INFER", "ASSUM"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Finiteness": {"feature": {"num_classes": 2, "names": ["FIN", "NFIN"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}, "Gender": {"feature": {"num_classes": 34, "names": ["MASC", "FEM", "NEUT", "NAKH1", "NAKH2", "NAKH3", "NAKH4", "NAKH5", "NAKH6", "NAKH7", "NAKH8", "BANTU1", "BANTU2", "BANTU3", "BANTU4", "BANTU5", "BANTU6", "BANTU7", "BANTU8", "BANTU9", 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diff --git a/universal_morphologies.py b/universal_morphologies.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.
+"""UniMorph: Universal Morphologies."""
+
+from __future__ import absolute_import, division, print_function
+
+import datasets
+
+
+_CITATION = """\
+@article{sylak2016composition,
+  title={The composition and use of the universal morphological feature schema (unimorph schema)},
+  author={Sylak-Glassman, John},
+  journal={Johns Hopkins University},
+  year={2016}
+}
+"""
+
+_DESCRIPTION = """\
+The Universal Morphology (UniMorph) project is a collaborative effort to improve how NLP handles complex morphology in the world’s languages.
+The goal of UniMorph is to annotate morphological data in a universal schema that allows an inflected word from any language to be defined by its lexical meaning,
+typically carried by the lemma, and by a rendering of its inflectional form in terms of a bundle of morphological features from our schema.
+The specification of the schema is described in Sylak-Glassman (2016).
+"""
+
+_HOMEPAGE = "https://unimorph.github.io/"
+
+_LICENSE = "CC-BY-SA-3.0"
+
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+    "nno": "https://raw.githubusercontent.com/unimorph/nno/master/nno",
+    "fas": "https://raw.githubusercontent.com/unimorph/fas/master/fas",
+    "pol": "https://raw.githubusercontent.com/unimorph/pol/master/pol",
+    "por": "https://raw.githubusercontent.com/unimorph/por/master/por",
+    "que": "https://raw.githubusercontent.com/unimorph/que/master/que",
+    "ron": "https://raw.githubusercontent.com/unimorph/ron/master/ron",
+    "rus": "https://raw.githubusercontent.com/unimorph/rus/master/rus",
+    "gla": "https://raw.githubusercontent.com/unimorph/gla/master/gla",
+    "slv": "https://raw.githubusercontent.com/unimorph/slv/master/slv",
+    "spa": "https://raw.githubusercontent.com/unimorph/spa/master/spa",
+    "swe": "https://raw.githubusercontent.com/unimorph/swe/master/swe",
+    "tur": "https://raw.githubusercontent.com/unimorph/tur/master/tur",
+    "ukr": "https://raw.githubusercontent.com/unimorph/ukr/master/ukr",
+    "urd": "https://raw.githubusercontent.com/unimorph/urd/master/urd",
+    "cym": "https://raw.githubusercontent.com/unimorph/cym/master/cym",
+    "yid": "https://raw.githubusercontent.com/unimorph/yid/master/yid",
+    "lud|mikhailovskoye": "https://raw.githubusercontent.com/unimorph/lud/master/lud-mikhailovskoye-dialect.txt",
+    "lud|new_written": "https://raw.githubusercontent.com/unimorph/lud/master/lud-new-written-ludian-dialect.txt",
+    "lud|southern_ludian_svjatozero": "https://raw.githubusercontent.com/unimorph/lud/master/lud-southern-ludian-svjatozero-dialect.txt",
+    "olo|kotkozero": "https://raw.githubusercontent.com/unimorph/olo/master/olo-kotkozero-dialect.txt",
+    "olo|new_written": "https://raw.githubusercontent.com/unimorph/olo/master/olo-new-written-livvic-dialect.txt",
+    "olo|syamozero": "https://raw.githubusercontent.com/unimorph/olo/master/olo-syamozero-dialect.txt",
+    "olo|vedlozero": "https://raw.githubusercontent.com/unimorph/olo/master/olo-vedlozero-dialect.txt",
+    "olo|vidlitsa": "https://raw.githubusercontent.com/unimorph/olo/master/olo-vidlitsa-dialect.txt",
+    "vep|central_eastern": "https://raw.githubusercontent.com/unimorph/vep/master/vep-central-eastern-veps.txt",
+    "vep|central_western": "https://raw.githubusercontent.com/unimorph/vep/master/vep-central-western-veps.txt",
+    "vep|new_written": "https://raw.githubusercontent.com/unimorph/vep/master/vep-new-written-veps.txt",
+    "vep|northern": "https://raw.githubusercontent.com/unimorph/vep/master/vep-northern-veps.txt",
+    "vep|southern": "https://raw.githubusercontent.com/unimorph/vep/master/vep-southern-veps.txt",
+}
+
+_LANGUAGES = sorted(set([ln.split("|")[0] for ln in _URLs]))
+
+# make multiple splits for the languages with several dialects
+_SPLITS = {}
+for ln in _URLs:
+    if "|" in ln:
+        ln_conf, ln_split = ln.split("|")
+        _SPLITS[ln_conf] = _SPLITS.get(ln_conf, []) + [ln_split]
+
+_CATEGORIES = {
+    "Aktionsart": ["STAT", "DYN", "TEL", "ATEL", "PCT", "DUR", "ACH", "ACCMP", "SEMEL", "ACTY"],
+    "Animacy": ["ANIM", "INAN", "HUM", "NHUM"],
+    "Argument_Marking": [
+        "ARGNO1S",
+        "ARGNO2S",
+        "ARGNO3S",
+        "ARGNO1P",
+        "ARGNO2P",
+        "ARGNO3P",
+        "ARGAC1S",
+        "ARGAC2S",
+        "ARGAC3S",
+        "ARGAC1P",
+        "ARGAC2P",
+        "ARGAC3P",
+        "ARGAB1S",
+        "ARGAB2S",
+        "ARGAB3S",
+        "ARGAB1P",
+        "ARGAB2P",
+        "ARGAB3P",
+        "ARGER1S",
+        "ARGER2S",
+        "ARGER3S",
+        "ARGER1P",
+        "ARGER2P",
+        "ARGER3P",
+        "ARGDA1S",
+        "ARGDA2S",
+        "ARGDA3S",
+        "ARGDA1P",
+        "ARGDA2P",
+        "ARGDA3P",
+        "ARGBE1S",
+        "ARGBE2S",
+        "ARGBE3S",
+        "ARGBE1P",
+        "ARGBE2P",
+        "ARGBE3P",
+    ],
+    "Aspect": ["IPFV", "PFV", "PRF", "PROG", "PROSP", "ITER", "HAB"],
+    "Case": [
+        "NOM",
+        "ACC",
+        "ERG",
+        "ABS",
+        "NOMS",
+        "DAT",
+        "BEN",
+        "PRP",
+        "GEN",
+        "REL",
+        "PRT",
+        "INS",
+        "COM",
+        "VOC",
+        "COMPV",
+        "EQTV",
+        "PRIV",
+        "PROPR",
+        "AVR",
+        "FRML",
+        "TRANS",
+        "BYWAY",
+        "INTER",
+        "AT",
+        "POST",
+        "IN",
+        "CIRC",
+        "ANTE",
+        "APUD",
+        "ON",
+        "ONHR",
+        "ONVR",
+        "SUB",
+        "REM",
+        "PROXM",
+        "ESS",
+        "ALL",
+        "ABL",
+        "APPRX",
+        "TERM",
+    ],
+    "Comparison": ["CMPR", "SPRL", "AB", "RL", "EQT"],
+    "Definiteness": ["DEF", "INDF", "SPEC", "NSPEC"],
+    "Deixis": ["PROX", "MED", "REMT", "REF1", "REF2", "NOREF", "PHOR", "VIS", "NVIS", "ABV", "EVEN", "BEL"],
+    "Evidentiality": ["FH", "DRCT", "SEN", "VISU", "NVSEN", "AUD", "NFH", "QUOT", "RPRT", "HRSY", "INFER", "ASSUM"],
+    "Finiteness": ["FIN", "NFIN"],
+    "Gender": [
+        "MASC",
+        "FEM",
+        "NEUT",
+        "NAKH1",
+        "NAKH2",
+        "NAKH3",
+        "NAKH4",
+        "NAKH5",
+        "NAKH6",
+        "NAKH7",
+        "NAKH8",
+        "BANTU1",
+        "BANTU2",
+        "BANTU3",
+        "BANTU4",
+        "BANTU5",
+        "BANTU6",
+        "BANTU7",
+        "BANTU8",
+        "BANTU9",
+        "BANTU10",
+        "BANTU11",
+        "BANTU12",
+        "BANTU13",
+        "BANTU14",
+        "BANTU15",
+        "BANTU16",
+        "BANTU17",
+        "BANTU18",
+        "BANTU19",
+        "BANTU20",
+        "BANTU21",
+        "BANTU22",
+        "BANTU23",
+    ],
+    "Information_Structure": ["TOP", "FOC"],
+    "Interrogativity": ["DECL", "INT"],
+    "Language_Specific": [
+        "LGSPEC1",
+        "LGSPEC2",
+        "LGSPEC3",
+        "LGSPEC4",
+        "LGSPEC5",
+        "LGSPEC6",
+        "LGSPEC7",
+        "LGSPEC8",
+        "LGSPEC9",
+        "LGSPEC10",
+    ],
+    "Mood": [
+        "IND",
+        "SBJV",
+        "REAL",
+        "IRR",
+        "AUPRP",
+        "AUNPRP",
+        "IMP",
+        "COND",
+        "PURP",
+        "INTEN",
+        "POT",
+        "LKLY",
+        "ADM",
+        "OBLIG",
+        "DEB",
+        "PERM",
+        "DED",
+        "SIM",
+        "OPT",
+    ],
+    "Number": ["SG", "PL", "GRPL", "DU", "TRI", "PAUC", "GRPAUC", "INVN"],
+    "Part_Of_Speech": [
+        "N",
+        "PROPN",
+        "ADJ",
+        "PRO",
+        "CLF",
+        "ART",
+        "DET",
+        "V",
+        "ADV",
+        "AUX",
+        "V.PTCP",
+        "V.MSDR",
+        "V.CVB",
+        "ADP",
+        "COMP",
+        "CONJ",
+        "NUM",
+        "PART",
+        "INTJ",
+    ],
+    "Person": ["0", "1", "2", "3", "4", "INCL", "EXCL", "PRX", "OBV"],
+    "Polarity": ["POS", "NEG"],
+    "Politeness": [
+        "INFM",
+        "FORM",
+        "ELEV",
+        "HUMB",
+        "POL",
+        "AVOID",
+        "LOW",
+        "HIGH",
+        "STELEV",
+        "STSUPR",
+        "LIT",
+        "FOREG",
+        "COL",
+    ],
+    "Possession": [
+        "ALN",
+        "NALN",
+        "PSS1S",
+        "PSS2S",
+        "PSS2SF",
+        "PSS2SM",
+        "PSS2SINFM",
+        "PSS2SFORM",
+        "PSS3S",
+        "PSS3SF",
+        "PSS3SM",
+        "PSS1D",
+        "PSS1DI",
+        "PSS1DE",
+        "PSS2D",
+        "PSS2DM",
+        "PSS2DF",
+        "PSS3D",
+        "PSS3DF",
+        "PSS3DM",
+        "PSS1P",
+        "PSS1PI",
+        "PSS1PE",
+        "PSS2P",
+        "PSS2PF",
+        "PSS2PM",
+        "PSS3PF",
+        "PSS3PM",
+    ],
+    "Switch_Reference": ["SS", "SSADV", "DS", "DSADV", "OR", "SIMMA", "SEQMA", "LOG"],
+    "Tense": ["PRS", "PST", "FUT", "IMMED", "HOD", "1DAY", "RCT", "RMT"],
+    "Valency": ["IMPRS", "INTR", "TR", "DITR", "REFL", "RECP", "CAUS", "APPL"],
+    "Voice": ["ACT", "MID", "PASS", "ANTIP", "DIR", "INV", "AGFOC", "PFOC", "LFOC", "BFOC", "ACFOC", "IFOC", "CFOC"],
+}
+
+_TAG_TO_CAT = dict([(tag, cat) for cat, tags in _CATEGORIES.items() for tag in tags])
+
+
+class UniversalMorphologies(datasets.GeneratorBasedBuilder):
+    """UniMorph: Universal Morphologies."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=f"{language_iso}",
+            version=datasets.Version("1.0.0"),
+            description=f"Universal Morphologies for {language_iso}",
+        )
+        for language_iso in _LANGUAGES
+    ]
+
+    DEFAULT_CONFIG_NAME = "ady"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "lemma": datasets.Value("string"),
+                "forms": datasets.Sequence(
+                    dict(
+                        [("word", datasets.Value("string"))]
+                        + [
+                            (cat, datasets.Sequence(datasets.ClassLabel(names=tasks)))
+                            for cat, tasks in _CATEGORIES.items()
+                        ]
+                        + [("Other", datasets.Sequence(datasets.Value("string")))]  # for misspecified tags
+                    )
+                ),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        config_urls = dict([(ln, f_url) for ln, f_url in _URLs.items() if ln.split("|")[0] == self.config.name])
+        data_dir = dl_manager.download_and_extract(config_urls)
+        if self.config.name in _SPLITS:
+            return [
+                datasets.SplitGenerator(
+                    name=spl,
+                    gen_kwargs={
+                        "filepath": data_dir[f"{self.config.name}|{spl}"],
+                    },
+                )
+                for spl in _SPLITS[self.config.name]
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "filepath": data_dir[self.config.name],
+                    },
+                )
+            ]
+
+    def _generate_examples(self, filepath):
+        all_forms = {}
+        # we need to do a full path first to gather all forms of a lemma
+        with open(filepath, encoding="utf-8") as f:
+            forms = []
+            for row in f:
+                if row.strip() == "" or row.strip().startswith("#"):
+                    continue
+                lemma, word, tags = row.strip().split("\t")
+                all_forms[lemma] = all_forms.get(lemma, [])
+                tag_list = tags.replace("NDEF", "INDF").split(";")
+                form = dict([("word", word), ("Other", [])] + [(cat, []) for cat, tasks in _CATEGORIES.items()])
+                for tag_pre in tag_list:
+                    tag = tag_pre.split("+")
+                    if tag[0] in _TAG_TO_CAT:
+                        form[_TAG_TO_CAT[tag[0]]] = tag
+                    else:
+                        form["Other"] += tag
+                all_forms[lemma] += [form]
+        for id_, (lemma, forms) in enumerate(all_forms.items()):
+            res = {"lemma": lemma, "forms": {}}
+            for k in ["word", "Other"] + list(_CATEGORIES.keys()):
+                res["forms"][k] = [form[k] for form in forms]
+            yield id_, res