update textclassifier

tasks/text.py

@@ -39,35 +39,31 @@ class TextClassifier:
         
         for attempt in range(max_retries):
             try:
-                # Load config with modified settings
-                self.config = AutoConfig.from_pretrained(
-                    model_name,
-                    num_labels=8,
-                    problem_type="single_label_classification",
-                    trust_remote_code=True
-                )
-                
-                # Remove problematic config attributes
-                if hasattr(self.config, 'norm_bias'):
-                    delattr(self.config, 'norm_bias')
-                if hasattr(self.config, 'bias'):
-                    delattr(self.config, 'bias')
-                
-                # Initialize tokenizer
+                # Initialize tokenizer first
                 self.tokenizer = AutoTokenizer.from_pretrained(
                     model_name,
                     model_max_length=8192,
                     padding_side='right',
-                    truncation_side='right',
-                    trust_remote_code=True
+                    truncation_side='right'
                 )
                 
-                # Initialize model with modified config
+                # Load base config
+                self.config = AutoConfig.from_pretrained(
+                    model_name,
+                    num_labels=8,
+                    problem_type="single_label_classification"
+                )
+                
+                # Set required attributes
+                self.config.hidden_size = 768
+                self.config.num_attention_heads = 12
+                self.config.num_hidden_layers = 12
+                self.config.norm_eps = 1e-5
+                
+                # Initialize model with basic config
                 self.model = AutoModelForSequenceClassification.from_pretrained(
                     model_name,
                     config=self.config,
-                    trust_remote_code=True,
-                    torch_dtype=torch.float32,
                     ignore_mismatched_sizes=True
                 )