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Use core lg models as vectors models in quickstart
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@ -2,7 +2,7 @@
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# Not all languages have recommended word vectors or transformers and for some,
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# the recommended transformer for efficiency and accuracy may be the same.
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en:
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word_vectors: en_vectors_web_lg
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word_vectors: en_core_web_lg
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transformer:
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efficiency:
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name: roberta-base
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@ -11,7 +11,7 @@ en:
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name: roberta-base
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size_factor: 3
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de:
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word_vectors: null
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word_vectors: de_core_news_lg
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transformer:
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efficiency:
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name: bert-base-german-cased
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@ -20,7 +20,7 @@ de:
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name: bert-base-german-cased
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size_factor: 3
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fr:
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word_vectors: null
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word_vectors: fr_core_news_lg
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transformer:
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efficiency:
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name: camembert-base
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@ -29,7 +29,7 @@ fr:
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name: camembert-base
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size_factor: 3
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es:
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word_vectors: null
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word_vectors: es_core_news_lg
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transformer:
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efficiency:
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name: dccuchile/bert-base-spanish-wwm-cased
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@ -56,7 +56,7 @@ fi:
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name: TurkuNLP/bert-base-finnish-cased-v1
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size_factor: 3
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el:
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word_vectors: null
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word_vectors: el_core_news_lg
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transformer:
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efficiency:
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name: nlpaueb/bert-base-greek-uncased-v1
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@ -74,7 +74,7 @@ tr:
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name: dbmdz/bert-base-turkish-cased
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size_factor: 3
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zh:
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word_vectors: null
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word_vectors: zh_core_web_lg
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transformer:
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efficiency:
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name: bert-base-chinese
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@ -93,7 +93,7 @@ ar:
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name: asafaya/bert-base-arabic
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size_factor: 3
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pl:
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word_vectors: null
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word_vectors: pl_core_news_lg
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transformer:
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efficiency:
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name: dkleczek/bert-base-polish-cased-v1
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@ -102,7 +102,7 @@ pl:
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name: dkleczek/bert-base-polish-cased-v1
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size_factor: 3
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nl:
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word_vectors: null
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word_vectors: nl_core_news_lg
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transformer:
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efficiency:
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name: pdelobelle/robbert-v2-dutch-base
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@ -111,7 +111,7 @@ nl:
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name: pdelobelle/robbert-v2-dutch-base
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size_factor: 3
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pt:
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word_vectors: null
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word_vectors: pt_core_news_lg
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transformer:
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efficiency:
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name: neuralmind/bert-base-portuguese-cased
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