class_model/model.py

import torch
import torch.nn as nn
from transformers import AutoTokenizer, AutoModelForSequenceClassification

class MyTinyBERT(nn.Module):
    def __init__(self):
        super().__init__()
        self.bert = AutoModelForSequenceClassification.from_pretrained('cointegrated/rubert-tiny-toxicity')
        for param in self.bert.parameters():
            param.requires_grad = False
        self.linear = nn.Sequential(
            nn.Linear(5, 256),
            nn.Sigmoid(),
            nn.Dropout(),
            nn.Linear(256, 512),
            nn.Sigmoid(),
            nn.Dropout(p=0.4),
            nn.Linear(512, 1)
        )

    def forward(self, x):
        bert_out = self.bert(x[0], attention_mask=x[1])
        normed_bert_out = nn.functional.normalize(bert_out.logits)
        out = self.linear(normed_bert_out)
        return out