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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] |