def load(cls, model_path: Union[str, Path]):
"""
Loads the model from the given file.
:param model_path: the model file
:return: the loaded text classifier model
"""
model_file = cls._fetch_model(str(model_path))
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
# load_big_file is a workaround byhttps://github.com/highway11git
# to load models on some Mac/Windows setups
# see https://github.com/zalandoresearch/flair/issues/351
f = file_utils.load_big_file(str(model_file))
state = torch.load(f, map_location="cpu")
model = cls._init_model_with_state_dict(state)
if "model_card" in state:
model.model_card = state["model_card"]
model.eval()
model.to(flair.device)
return model
def load_flair_upos_fast():
"""Loads flair 'upos-fast' SequenceTagger.
This is a temporary workaround for flair v0.6. Will be fixed when
flair pushes the bug fix.
"""
import pathlib
import warnings
from flair import file_utils
import torch
hu_path: str = "https://nlp.informatik.hu-berlin.de/resources/models"
upos_path = "/".join([hu_path, "upos-fast", "en-upos-ontonotes-fast-v0.4.pt"])
model_path = file_utils.cached_path(upos_path, cache_dir=pathlib.Path("models"))
model_file = SequenceTagger._fetch_model(model_path)
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
# load_big_file is a workaround by https://github.com/highway11git to load models on some Mac/Windows setups
# see https://github.com/zalandoresearch/flair/issues/351
f = file_utils.load_big_file(str(model_file))
state = torch.load(f, map_location="cpu")
model = SequenceTagger._init_model_with_state_dict(state)
model.eval()
model.to(textattack.shared.utils.device)
return model