# Recommended settings and available resources for each language, if available.
# Not all languages have recommended word vectors or transformers and for some,
# the recommended transformer for efficiency and accuracy may be the same.
__default__:
  word_vectors: null
  transformer:
    efficiency:
      name: bert-base-multilingual-uncased
      size_factor: 3
    accuracy:
      name: bert-base-multilingual-uncased
      size_factor: 3
ar:
  word_vectors: null
  transformer:
    efficiency:
      name: asafaya/bert-base-arabic
      size_factor: 3
    accuracy:
      name: asafaya/bert-base-arabic
      size_factor: 3
da:
  word_vectors: da_core_news_lg
  transformer: null
de:
  word_vectors: de_core_news_lg
  transformer:
    efficiency:
      name: bert-base-german-cased
      size_factor: 3
    accuracy:
      name: bert-base-german-cased
      size_factor: 3
el:
  word_vectors: el_core_news_lg
  transformer:
    efficiency:
      name: nlpaueb/bert-base-greek-uncased-v1
      size_factor: 3
    accuracy:
      name: nlpaueb/bert-base-greek-uncased-v1
      size_factor: 3
en:
  word_vectors: en_core_web_lg
  transformer:
    efficiency:
      name: roberta-base
      size_factor: 3
    accuracy:
      name: roberta-base
      size_factor: 3
es:
  word_vectors: es_core_news_lg
  transformer:
    efficiency:
      name: dccuchile/bert-base-spanish-wwm-cased
      size_factor: 3
    accuracy:
      name: dccuchile/bert-base-spanish-wwm-cased
      size_factor: 3
fi:
  word_vectors: null
  transformer:
    efficiency:
      name: TurkuNLP/bert-base-finnish-cased-v1
      size_factor: 3
    accuracy:
      name: TurkuNLP/bert-base-finnish-cased-v1
      size_factor: 3
fr:
  word_vectors: fr_core_news_lg
  transformer:
    efficiency:
      name: camembert-base
      size_factor: 3
    accuracy:
      name: camembert-base
      size_factor: 3
it:
  word_vectors: it_core_news_lg
  transformers: null
ja:
  word_vectors: ja_core_news_lg
  transformers: null
lt:
  word_vectors: lt_core_news_lg
  transformers: null
nb:
  word_vectors: nb_core_news_lg
  transformers: null
nl:
  word_vectors: nl_core_news_lg
  transformer:
    efficiency:
      name: pdelobelle/robbert-v2-dutch-base
      size_factor: 3
    accuracy:
      name: pdelobelle/robbert-v2-dutch-base
      size_factor: 3
pl:
  word_vectors: pl_core_news_lg
  transformer:
    efficiency:
      name: dkleczek/bert-base-polish-cased-v1
      size_factor: 3
    accuracy:
      name: dkleczek/bert-base-polish-cased-v1
      size_factor: 3
pt:
  word_vectors: pt_core_news_lg
  transformer:
    efficiency:
      name: neuralmind/bert-base-portuguese-cased
      size_factor: 3
    accuracy:
      name: neuralmind/bert-base-portuguese-cased
      size_factor: 3
ro:
  word_vectors: ro_core_news_lg
  transformers: null
sv:
  word_vectors: null
  transformer:
    efficiency:
      name: KB/bert-base-swedish-cased
      size_factor: 3
    accuracy:
      name: KB/bert-base-swedish-cased
      size_factor: 3
tr:
  word_vectors: null
  transformer:
    efficiency:
      name: dbmdz/bert-base-turkish-cased
      size_factor: 3
    accuracy:
      name: dbmdz/bert-base-turkish-cased
      size_factor: 3
zh:
  word_vectors: zh_core_web_lg
  transformer:
    efficiency:
      name: bert-base-chinese
      size_factor: 3
    accuracy:
      name: bert-base-chinese
      size_factor: 3
  has_letters: false