Remove HFAbRestore.restore override to use original AbRestore.restore method

adapter.py

@@ -558,35 +558,6 @@ class HFAbRestore(AbRestore):
                 return output.last_hidden_state
             return output
         return model_call
-    
-    def restore(self, seqs, align=False, **kwargs):
-        """Restore masked residues in antibody sequences."""
-        if isinstance(seqs, str):
-            seqs = [seqs]
-        
-        # Use the original AbLang2 restore logic
-        # Tokenize sequences using original interface
-        tokens = self.tokenizer(seqs, pad=True, w_extra_tkns=False, device=self.used_device)
-        
-        # Get predictions for amino acids (indices 1-20)
-        predictions = self.AbLang(tokens)[:,:,1:21]
-        
-        # Find predicted tokens and replace mask tokens
-        predicted_tokens = torch.max(predictions, -1).indices + 1
-        restored_tokens = torch.where(tokens==23, predicted_tokens, tokens)
-        
-        # Decode back to sequences using original tokenizer
-        restored_seqs = self.tokenizer(restored_tokens, mode="decode")
-        
-        # Handle paired sequences format
-        n_seqs = len(seqs)
-        if n_seqs < len(restored_seqs):
-            restored_seqs = [f"{h}|{l}".replace('-','') for h,l in zip(restored_seqs[:n_seqs], restored_seqs[n_seqs:])]
-            seqs = [f"{h}|{l}" for h,l in zip(seqs[:n_seqs], seqs[n_seqs:])]
-        
-        # Apply final formatting
-        from extra_utils import res_to_seq
-        return np.array([res_to_seq(seq, 'restore') for seq in np.c_[restored_seqs, np.vectorize(len)(seqs)]])
 
 def add_angle_brackets(seq):
     # Assumes input is 'VH|VL' or 'VH|' or '|VL'