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