def load(self, device):
"""
Load user-selected task-specific model
Args:
device (str): device information
Returns:
object: User-selected task-specific model
"""
if "roberta" in self.config.n_model:
from pororo.models.brainbert import CustomRobertaModel
model = (CustomRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerEn(model, self.config)
if "charbert" in self.config.n_model:
from pororo.models.brainbert import CharBrainRobertaModel
from pororo.tasks.tokenization import PororoTokenizationFactory
model = (CharBrainRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
sent_tokenizer = PororoTokenizationFactory(
task="tokenization",
model="sent_ko",
lang=self.config.lang,
).load(device)
return PororoBertCharNer(
model,
sent_tokenizer,
device,
self.config,
)
if "zhberta" in self.config.n_model:
from pororo.models.brainbert import ZhbertaModel
model = (ZhbertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerZh(model, self.config)
if "jaberta" in self.config.n_model:
from pororo.models.brainbert import JabertaModel
model = (JabertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerJa(model, self.config)
def load(self, device: str):
"""
Load user-selected task-specific model
Args:
device (str): device information
Returns:
object: User-selected task-specific model
"""
if "brainbert" in self.config.n_model:
from pororo.models.brainbert import BrainRobertaModel
model = (BrainRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertSts(model, self.config)
if "jaberta" in self.config.n_model:
from pororo.models.brainbert import JabertaModel
model = (JabertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertSts(model, self.config)
if "zhberta" in self.config.n_model:
from pororo.models.brainbert import ZhbertaModel
model = (ZhbertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertSts(model, self.config)
if "sbert" in self.config.n_model:
from sentence_transformers import SentenceTransformer
path = download_or_load(
f"sbert/{self.config.n_model}",
self.config.lang,
)
model = SentenceTransformer(path).eval().to(device)
return PororoSBertSts(model, self.config)
if "roberta" in self.config.n_model:
from pororo.models.brainbert import CustomRobertaModel
model = (CustomRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertSts(model, self.config)
def load(self, device: str):
"""
Load user-selected task-specific model
Args:
device (str): device information
Returns:
object: User-selected task-specific model
"""
if "roberta" in self.config.n_model:
from pororo.models.brainbert import CustomRobertaModel
model = (CustomRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertBlank(model, self.config)
if "posbert" in self.config.n_model:
try:
import mecab # noqa
except ModuleNotFoundError as error:
raise error.__class__(
"Please install python-mecab-ko with: `pip install python-mecab-ko`"
)
from pororo.models.brainbert import PosRobertaModel
model = (PosRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertBlank(model, self.config)
if "jaberta" in self.config.n_model:
from pororo.models.brainbert import JabertaModel
model = (JabertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertBlank(model, self.config)
if "zhberta" in self.config.n_model:
from pororo.models.brainbert import ZhbertaModel
model = (ZhbertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertBlank(model, self.config)
def load(self, device: str):
"""
Load user-selected task-specific model
Args:
device (str): device information
Returns:
object: User-selected task-specific model
"""
if "brainbert" in self.config.n_model:
from pororo.models.brainbert import BrainRobertaModel
model = (BrainRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertReviewScore(model, self.config)
if "roberta" in self.config.n_model:
from pororo.models.brainbert import CustomRobertaModel
model = (CustomRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertReviewScore(model, self.config)
if "jaberta" in self.config.n_model:
from pororo.models.brainbert import JabertaModel
model = (JabertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertReviewScore(model, self.config)
if "zhberta" in self.config.n_model:
from pororo.models.brainbert import ZhbertaModel
model = (ZhbertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertReviewScore(model, self.config)
def load(self, device):
"""
Load user-selected task-specific model
Args:
device (str): device information
Returns:
object: User-selected task-specific model
"""
if "roberta" in self.config.n_model:
from pororo.models.brainbert import CustomRobertaModel
model = (CustomRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerEn(model, self.config)
if "charbert" in self.config.n_model:
from pororo.models.brainbert import CharBrainRobertaModel
from pororo.tasks.tokenization import PororoTokenizationFactory
model = (CharBrainRobertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
sent_tokenizer = PororoTokenizationFactory(
task="tokenization",
model="sent_ko",
lang=self.config.lang,
).load(device)
f_wsd_dict = open(
download_or_load(
f"misc/wiki.{self.config.lang}.items",
self.config.lang,
),
"r",
)
wsd_dict = defaultdict(dict)
for line in f_wsd_dict.readlines():
origin, target, word = line.strip().split("\t")
wsd_dict[origin][word] = target
return PororoBertCharNer(
model,
sent_tokenizer,
wsd_dict,
device,
self.config,
)
if "zhberta" in self.config.n_model:
from pororo.models.brainbert import ZhbertaModel
model = (ZhbertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerZh(model, self.config)
if "jaberta" in self.config.n_model:
from pororo.models.brainbert import JabertaModel
model = (JabertaModel.load_model(
f"bert/{self.config.n_model}",
self.config.lang,
).eval().to(device))
return PororoBertNerJa(model, self.config)
