The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 141 new columns ({'tamil', 'sme', 'uk', 'orv', 'nn', 'lv', 'be', 'thai', 'af', 'gl', 'sk', 'turkish', 'ancient_greek', 'indonesian', 'livvi', 'scottish_gaelic', 'es', 'norwegian_bokmaal', 'lzh', 'id', 'classical_chinese', 'italian', 'spanish', 'coptic', 'bulgarian', 'he', 'ko', 'czech', 'fa', 'fro', 'dutch', 'ga', 'cu', 'north_sami', 'ar', 'cop', 'tr', 'french', 'mr', 'kmr', 'zh-hans', 'buryat', 'kurmanji', 'vi', 'zh', 'wolof', 'gothic', 'eu', 'hy', 'upper_sorbian', 'slovenian', 'hindi', 'nb', 'ca', 'olo', 'old_russian', 'sv', 'telugu', 'fr', 'serbian', 'hebrew', 'lithuanian', 'galician', 'irish', 'ru', 'belarusian', 'simplified_chinese', 'latvian', 'it', 'en', 'et', 'bxr', 'th', 'ug', 'ro', 'el', 'fi', 'te', 'latin', 'danish', 'croatian', 'pl', 'swl', 'catalan', 'cs', 'armenian', 'la', 'marathi', 'uyghur', 'got', 'hsb', 'arabic', 'da', 'greek', 'ta', 'russian', 'wo', 'finnish', 'zh-hant', 'ja', 'estonian', 'lt', 'mt', 'vietnamese', 'sl', 'traditional_chinese', 'norwegian_nynorsk', 'romanian', 'german', 'basque', 'sr', 'swedish', 'ur', 'hi', 'persian', 'old_french', 'maltese', 'kk', 'portuguese', 'no', 'japanese', 'pt', 'english', 'nl', 'hungarian', 'bg', 'old_church_slavonic', 'urdu', 'grc', 'slovak', 'kazakh', 'hu', 'polish', 'afrikaans', 'korean', 'swedish_sign_language', 'gd', 'ukrainian', 'url', 'de', 'hr'}) and 6 missing columns ({'to_name', 'to_code', 'from_code', 'from_name', 'package_version', 'argos_version'}).
This happened while the json dataset builder was generating data using
hf://datasets/GeorgeSpark/translationmodels/en_ja/stanza/resources.json (at revision 601abf1a8a103e0f46a1f3761d22bfa71540909c)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
ar: struct<backward_charlm: struct<ccwiki: struct<md5: string>>, forward_charlm: struct<ccwiki: struct<md5: string>>, depparse: struct<padt: struct<md5: string, dependencies: list<item: struct<model: string, package: string>>>>, lemma: struct<padt: struct<md5: string>>, mwt: struct<padt: struct<md5: string>>, ner: struct<aqmar: struct<md5: string, dependencies: list<item: struct<model: string, package: string>>>>, pos: struct<padt: struct<md5: string, dependencies: list<item: struct<model: string, package: string>>>>, pretrain: struct<padt: struct<md5: string>>, tokenize: struct<padt: struct<md5: string>>, default_processors: struct<tokenize: string, mwt: string, lemma: string, pos: string, depparse: string, ner: string>, default_dependencies: struct<pos: list<item: struct<model: string, package: string>>, depparse: list<item: struct<model: string, package: string>>, ner: list<item: struct<model: string, package: string>>>, default_md5: string, lang_name: string>
child 0, backward_charlm: struct<ccwiki: struct<md5: string>>
child 0, ccwiki: struct<md5: string>
child 0, md5: string
child 1, forward_charlm: struct<ccwiki: struct<md5: string>>
child 0, ccwiki: struct<md5: string>
child 0, md5: string
child 2, depparse: struct<padt: struct<md5: string, dependencies: list<item: struct<model: string, package: string>>>>
child 0, padt: struct<md5: string, dependencies: list<item: struct<model: string, package: string>>>
child 0,
...
st<item: struct<model: string, package: string>>
child 0, item: struct<model: string, package: string>
child 0, model: string
child 1, package: string
child 3, pretrain: struct<gsd: struct<md5: string>>
child 0, gsd: struct<md5: string>
child 0, md5: string
child 4, tokenize: struct<gsd: struct<md5: string>>
child 0, gsd: struct<md5: string>
child 0, md5: string
child 5, default_processors: struct<tokenize: string, lemma: string, pos: string, depparse: string>
child 0, tokenize: string
child 1, lemma: string
child 2, pos: string
child 3, depparse: string
child 6, default_dependencies: struct<pos: list<item: struct<model: string, package: string>>, depparse: list<item: struct<model: string, package: string>>>
child 0, pos: list<item: struct<model: string, package: string>>
child 0, item: struct<model: string, package: string>
child 0, model: string
child 1, package: string
child 1, depparse: list<item: struct<model: string, package: string>>
child 0, item: struct<model: string, package: string>
child 0, model: string
child 1, package: string
child 7, default_md5: string
child 8, lang_name: string
traditional_chinese: struct<alias: string>
child 0, alias: string
no: struct<alias: string>
child 0, alias: string
zh: struct<alias: string>
child 0, alias: string
url: string
to
{'package_version': Value(dtype='string', id=None), 'argos_version': Value(dtype='string', id=None), 'from_code': Value(dtype='string', id=None), 'from_name': Value(dtype='string', id=None), 'to_code': Value(dtype='string', id=None), 'to_name': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 141 new columns ({'tamil', 'sme', 'uk', 'orv', 'nn', 'lv', 'be', 'thai', 'af', 'gl', 'sk', 'turkish', 'ancient_greek', 'indonesian', 'livvi', 'scottish_gaelic', 'es', 'norwegian_bokmaal', 'lzh', 'id', 'classical_chinese', 'italian', 'spanish', 'coptic', 'bulgarian', 'he', 'ko', 'czech', 'fa', 'fro', 'dutch', 'ga', 'cu', 'north_sami', 'ar', 'cop', 'tr', 'french', 'mr', 'kmr', 'zh-hans', 'buryat', 'kurmanji', 'vi', 'zh', 'wolof', 'gothic', 'eu', 'hy', 'upper_sorbian', 'slovenian', 'hindi', 'nb', 'ca', 'olo', 'old_russian', 'sv', 'telugu', 'fr', 'serbian', 'hebrew', 'lithuanian', 'galician', 'irish', 'ru', 'belarusian', 'simplified_chinese', 'latvian', 'it', 'en', 'et', 'bxr', 'th', 'ug', 'ro', 'el', 'fi', 'te', 'latin', 'danish', 'croatian', 'pl', 'swl', 'catalan', 'cs', 'armenian', 'la', 'marathi', 'uyghur', 'got', 'hsb', 'arabic', 'da', 'greek', 'ta', 'russian', 'wo', 'finnish', 'zh-hant', 'ja', 'estonian', 'lt', 'mt', 'vietnamese', 'sl', 'traditional_chinese', 'norwegian_nynorsk', 'romanian', 'german', 'basque', 'sr', 'swedish', 'ur', 'hi', 'persian', 'old_french', 'maltese', 'kk', 'portuguese', 'no', 'japanese', 'pt', 'english', 'nl', 'hungarian', 'bg', 'old_church_slavonic', 'urdu', 'grc', 'slovak', 'kazakh', 'hu', 'polish', 'afrikaans', 'korean', 'swedish_sign_language', 'gd', 'ukrainian', 'url', 'de', 'hr'}) and 6 missing columns ({'to_name', 'to_code', 'from_code', 'from_name', 'package_version', 'argos_version'}).
This happened while the json dataset builder was generating data using
hf://datasets/GeorgeSpark/translationmodels/en_ja/stanza/resources.json (at revision 601abf1a8a103e0f46a1f3761d22bfa71540909c)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
package_version
string | argos_version
string | from_code
string | from_name
string | to_code
string | to_name
string | ar
dict | arabic
dict | de
dict | german
dict | en
dict | english
dict | es
dict | spanish
dict | fr
dict | french
dict | nl
dict | dutch
dict | ru
dict | russian
dict | zh-hans
dict | simplified_chinese
dict | af
dict | afrikaans
dict | be
dict | belarusian
dict | bg
dict | bulgarian
dict | bxr
dict | buryat
dict | ca
dict | catalan
dict | cop
dict | coptic
dict | cs
dict | czech
dict | cu
dict | old_church_slavonic
dict | da
dict | danish
dict | el
dict | greek
dict | et
dict | estonian
dict | eu
dict | basque
dict | fa
dict | persian
dict | fi
dict | finnish
dict | fro
dict | old_french
dict | ga
dict | irish
dict | gd
dict | scottish_gaelic
dict | gl
dict | galician
dict | got
dict | gothic
dict | grc
dict | ancient_greek
dict | he
dict | hebrew
dict | hi
dict | hindi
dict | hr
dict | croatian
dict | hsb
dict | upper_sorbian
dict | hu
dict | hungarian
dict | hy
dict | armenian
dict | id
dict | indonesian
dict | it
dict | italian
dict | ja
dict | japanese
dict | kk
dict | kazakh
dict | kmr
dict | kurmanji
dict | ko
dict | korean
dict | la
dict | latin
dict | lt
dict | lithuanian
dict | lv
dict | latvian
dict | lzh
dict | classical_chinese
dict | mr
dict | marathi
dict | mt
dict | maltese
dict | nn
dict | norwegian_nynorsk
dict | nb
dict | norwegian_bokmaal
dict | olo
dict | livvi
dict | orv
dict | old_russian
dict | pl
dict | polish
dict | pt
dict | portuguese
dict | ro
dict | romanian
dict | sk
dict | slovak
dict | sl
dict | slovenian
dict | sme
dict | north_sami
dict | sr
dict | serbian
dict | sv
dict | swedish
dict | swl
dict | swedish_sign_language
dict | ta
dict | tamil
dict | te
dict | telugu
dict | th
dict | thai
dict | tr
dict | turkish
dict | ug
dict | uyghur
dict | uk
dict | ukrainian
dict | ur
dict | urdu
dict | vi
dict | vietnamese
dict | wo
dict | wolof
dict | zh-hant
dict | traditional_chinese
dict | no
dict | zh
dict | url
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1.1 | 1.1 | en | English | ja | Japanese | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | null | null | {"backward_charlm":{"ccwiki":{"md5":"a6bd5a290149d920e7fe8c1da4d7e25b"}},"forward_charlm":{"ccwiki":(...TRUNCATED) | {
"alias": "ar"
} | {"backward_charlm":{"newswiki":{"md5":"82f0d9a6a12c736648edbe28d87e9016"}},"forward_charlm":{"newswi(...TRUNCATED) | {
"alias": "de"
} | {"backward_charlm":{"1billion":{"md5":"1405948b125b4264fd17509d1b6175ca"},"mimic":{"md5":"19a16ba4b8(...TRUNCATED) | {
"alias": "en"
} | {"backward_charlm":{"newswiki":{"md5":"acd1d5f0acc5ef8ccbac8576f1676503"}},"forward_charlm":{"newswi(...TRUNCATED) | {
"alias": "es"
} | {"backward_charlm":{"newswiki":{"md5":"42eba035046673e195274f45e713653c"}},"forward_charlm":{"newswi(...TRUNCATED) | {
"alias": "fr"
} | {"backward_charlm":{"ccwiki":{"md5":"217bcb073b6a5011e684ef8f1ddfb968"}},"forward_charlm":{"ccwiki":(...TRUNCATED) | {
"alias": "nl"
} | {"backward_charlm":{"newswiki":{"md5":"47d7517555684206f327ba4e0527d034"}},"forward_charlm":{"newswi(...TRUNCATED) | {
"alias": "ru"
} | {"backward_charlm":{"gigaword":{"md5":"9efba48c365d8ad4dfd62587578fa132"}},"forward_charlm":{"gigawo(...TRUNCATED) | {
"alias": "zh-hans"
} | {"depparse":{"afribooms":{"md5":"c8d6410c6ec7437e07b70751156b9211","dependencies":[{"model":"pretrai(...TRUNCATED) | {
"alias": "af"
} | {"depparse":{"hse":{"md5":"25dfb867053bf31600c9fb547cd9ee2a","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "be"
} | {"depparse":{"btb":{"md5":"ddf666ab61c253ff8b2a92945524cd2e","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "bg"
} | {"depparse":{"bdt":{"md5":"12301d68999309503f7e5fefd42f55b9","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "bxr"
} | {"depparse":{"ancora":{"md5":"3cd02727968bf9fcc41f0ce71f763c56","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "ca"
} | {"depparse":{"scriptorium":{"md5":"220899cfe651d2a103e02c4516c65040"}},"lemma":{"scriptorium":{"md5"(...TRUNCATED) | {
"alias": "cop"
} | {"depparse":{"cac":{"md5":"dcdd27e7680d3a2db2670e5e08b1b079","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "cs"
} | {"depparse":{"proiel":{"md5":"a3000d33c8f15a1d1e43715003b96d81","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "cu"
} | {"depparse":{"ddt":{"md5":"fd3138358cc1855e054498cf11445616","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "da"
} | {"depparse":{"gdt":{"md5":"5d8b2a51ed363c441fd9895ce0a54756","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "el"
} | {"depparse":{"edt":{"md5":"be9e8f12e52198211e6c4e6eb45c03ce","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "et"
} | {"depparse":{"bdt":{"md5":"f69d4045653a7f76fa490a43b9035cf3","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "eu"
} | {"depparse":{"seraji":{"md5":"c3a03301089c740262eb0276ad4bfd2a","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "fa"
} | {"depparse":{"ftb":{"md5":"bb2dcd7d8be332ac38f9a2d842887813","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "fi"
} | {"depparse":{"srcmf":{"md5":"5c33458d8bc40eba4985af3f7e2eac27","dependencies":[{"model":"pretrain","(...TRUNCATED) | {
"alias": "fro"
} | {"depparse":{"idt":{"md5":"756e74f349bf0176904d96fa65ae05c7","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "ga"
} | {"depparse":{"arcosg":{"md5":"0e9b859c8c867bd6f3d4c7986d230e10","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "gd"
} | {"depparse":{"ctg":{"md5":"2784179b5ea224f451cde93d99babc73","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "gl"
} | {"depparse":{"proiel":{"md5":"f9e5760ebe1a8ebe933fa7a2248e92d9","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "got"
} | {"depparse":{"perseus":{"md5":"d8a055510bb8a0b847d50e348765118a","dependencies":[{"model":"pretrain"(...TRUNCATED) | {
"alias": "grc"
} | {"depparse":{"htb":{"md5":"106ada8e20c8856d5e1e7693e99ead05","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "he"
} | {"depparse":{"hdtb":{"md5":"50d3dcaef001037ad6ef2dcdf86dfc97","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "hi"
} | {"depparse":{"set":{"md5":"e51b4f62d5256288265c7916815e4679","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "hr"
} | {"depparse":{"ufal":{"md5":"e66ab0c430b2f1ceaea0b1797c08ef21","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "hsb"
} | {"depparse":{"szeged":{"md5":"6789f06dbb6190224f051ceaece20400","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "hu"
} | {"depparse":{"armtdp":{"md5":"97480899830157d81cfde70077a53336","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "hy"
} | {"depparse":{"gsd":{"md5":"5d62d3bdbec2df1c38d913eb57f38571","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "id"
} | {"depparse":{"isdt":{"md5":"d9299667bc1c3e665d31eb00435af189","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "it"
} | {"depparse":{"gsd":{"md5":"d62dd92d5861365aef229cbb827c2555","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "ja"
} | {"depparse":{"ktb":{"md5":"3433c67ff4b209542429acc73eee101a","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "kk"
} | {"depparse":{"mg":{"md5":"8ebea8cf57387e78fe2bef7a028882f5","dependencies":[{"model":"pretrain","pac(...TRUNCATED) | {
"alias": "kmr"
} | {"depparse":{"gsd":{"md5":"26e37dfe8c35c9991d8cb5a3ef95c533","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "ko"
} | {"depparse":{"ittb":{"md5":"86709054294657828d8905a888b85933","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "la"
} | {"depparse":{"alksnis":{"md5":"c055cd6a85a7480f8bfe89197cc01d47","dependencies":[{"model":"pretrain"(...TRUNCATED) | {
"alias": "lt"
} | {"depparse":{"lvtb":{"md5":"fb8fc55e60660415dcdd71efe3f23d8a","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "lv"
} | {"depparse":{"kyoto":{"md5":"87d739419339e7f1cf99f108ba65270f","dependencies":[{"model":"pretrain","(...TRUNCATED) | {
"alias": "lzh"
} | {"depparse":{"ufal":{"md5":"734df4dda27136859cd11b61ece5044a","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "mr"
} | {"depparse":{"mudt":{"md5":"9408df2a1a5aab897508062fef20f39b","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "mt"
} | {"depparse":{"nynorsk":{"md5":"48559c93aa1976c0843a8bcf21d2c045","dependencies":[{"model":"pretrain"(...TRUNCATED) | {
"alias": "nn"
} | {"depparse":{"bokmaal":{"md5":"8cc47174844d85f27598ac908b5829bd","dependencies":[{"model":"pretrain"(...TRUNCATED) | {
"alias": "nb"
} | {"depparse":{"kkpp":{"md5":"d70964ac7c6df6a53138ce44155bde0f","dependencies":[{"model":"pretrain","p(...TRUNCATED) | {
"alias": "olo"
} | {"depparse":{"torot":{"md5":"add1c84eaa2f8e009e657de2b5a281a4"}},"lemma":{"torot":{"md5":"6d390806fa(...TRUNCATED) | {
"alias": "orv"
} | {"depparse":{"lfg":{"md5":"9bc6038a71540504d6c59711b7af93ea","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "pl"
} | {"depparse":{"bosque":{"md5":"314934b3fb237d450124c34378bb3841","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "pt"
} | {"depparse":{"nonstandard":{"md5":"5d246f49ad580e1ebbc575a024af00ca","dependencies":[{"model":"pretr(...TRUNCATED) | {
"alias": "ro"
} | {"depparse":{"snk":{"md5":"9833f9c25092b855485e96a6db163f07","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "sk"
} | {"depparse":{"ssj":{"md5":"eb10cbde390cf5f671119a06610effb5","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "sl"
} | {"depparse":{"giella":{"md5":"d719142327ad4e1e6b913acb430416b1","dependencies":[{"model":"pretrain",(...TRUNCATED) | {
"alias": "sme"
} | {"depparse":{"set":{"md5":"d33b7794836814ef5309671b73f89c6f","dependencies":[{"model":"pretrain","pa(...TRUNCATED) | {
"alias": "sr"
} | {"depparse":{"lines":{"md5":"084057aabc92d4fc32defa340e2a0c90","dependencies":[{"model":"pretrain","(...TRUNCATED) | {
"alias": "sv"
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1.4 | 1.4 | en | English | nl | Dutch | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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1.1 | 1.1 | en | English | zh | Chinese | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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1.1 | 1.1 | ja | Japanese | en | English | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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} | http://nlp.stanford.edu/software/stanza |
End of preview.