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Sort and add vectors for langs without transformers

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This commit is contained in:
Adriane Boyd 2020-10-16 08:25:16 +02:00
parent 2fbd43c603
commit c8d04b79e2
1 changed files with 75 additions and 57 deletions
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132
spacy/cli/templates/quickstart_training_recommendations.yml
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@ -1,15 +1,18 @@
# 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.
en:
word_vectors: en_core_web_lg
ar:
word_vectors: null
transformer:
efficiency:
name: roberta-base
name: asafaya/bert-base-arabic
size_factor: 3
accuracy:
name: roberta-base
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:
@ -19,14 +22,23 @@ de:
accuracy:
name: bert-base-german-cased
size_factor: 3
fr:
word_vectors: fr_core_news_lg
el:
word_vectors: el_core_news_lg
transformer:
efficiency:
name: camembert-base
name: nlpaueb/bert-base-greek-uncased-v1
size_factor: 3
accuracy:
name: camembert-base
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
@ -37,15 +49,6 @@ es:
accuracy:
name: dccuchile/bert-base-spanish-wwm-cased
size_factor: 3
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
fi:
word_vectors: null
transformer:
@ -55,14 +58,65 @@ fi:
accuracy:
name: TurkuNLP/bert-base-finnish-cased-v1
size_factor: 3
el:
word_vectors: el_core_news_lg
fr:
word_vectors: fr_core_news_lg
transformer:
efficiency:
name: nlpaueb/bert-base-greek-uncased-v1
name: camembert-base
size_factor: 3
accuracy:
name: nlpaueb/bert-base-greek-uncased-v1
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
@ -83,39 +137,3 @@ zh:
name: bert-base-chinese
size_factor: 3
has_letters: false
ar:
word_vectors: null
transformer:
efficiency:
name: asafaya/bert-base-arabic
size_factor: 3
accuracy:
name: asafaya/bert-base-arabic
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
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
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