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import torch
import torch.nn as nn
from transformers import AutoModel
class AbusePatternDetector(nn.Module):
def __init__(self, model_name, num_labels):
super().__init__()
self.bert = AutoModel.from_pretrained(model_name)
self.dropout = nn.Dropout(0.3)
self.classifier = nn.Linear(self.bert.config.hidden_size, num_labels)
def forward(self, input_ids, attention_mask):
outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask)
pooled_output = outputs.last_hidden_state[:, 0] # Use [CLS] token
pooled_output = self.dropout(pooled_output)
logits = self.classifier(pooled_output)
return logits
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