def pretrained(name="spell_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(NorvigSweetingModel, name,
language, remote_loc)
def pretrained(name="pos_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(PerceptronModel, name,
language, remote_loc)
def pretrained(name="vivekn_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(ViveknSentimentModel, name,
language, remote_loc)
def pretrained(name="context_spell_gen", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(ContextSpellCheckerModel, name,
language, remote_loc)
def pretrained(name="lemma_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(LemmatizerModel, name,
language, remote_loc)
def pretrained(name="spell_sd_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(SymmetricDeleteModel, name,
language, remote_loc)
def pretrained(name="ner_precise", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(NerDLModel, name, language,
remote_loc)
def pretrained(name="as_fast_lg", language="en"):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(AssertionLogRegModel, name,
language)
def pretrained(name="ner_fast", language="en"):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(NerCrfModel, name, language)
def pretrained(name="bert_uncased", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(BertEmbeddings, name, language,
remote_loc)
def pretrained(name="glove_100d", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(WordEmbeddingsModel, name,
language, remote_loc)
def pretrained(name="tdp_fast", language="en", remote_loc=None):
from sparknlp.pretrained import ResourceDownloader
return ResourceDownloader.downloadModel(TypedDependencyParserModel,
name, language, remote_loc)