nlp-project / models /LogReg.py
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import pandas as pd
import torch
import joblib
from models.preprocess_stage.bert_model import preprocess_bert
from models.preprocess_stage.bert_model import model
MAX_LEN = 100 # позже добавлю способ пользователю самому выбирать масимальную длину
# DEVICE='cpu'
logreg = joblib.load('models/weights/LogRegBestWeights.sav')
def predict_1(text):
preprocessed_text, attention_mask = preprocess_bert(text, MAX_LEN=MAX_LEN)
preprocessed_text, attention_mask = torch.tensor(preprocessed_text).unsqueeze(0), torch.tensor([attention_mask])
# model.to(DEVICE)
with torch.inference_mode():
vector = model(preprocessed_text, attention_mask=attention_mask)[0][:, 0, :]
predict = logreg.predict(vector)
return predict[-1]