Convert iic/speech_campplus_sv_zh_en_16k-common_advanced to MLX format

config.json

@@ -8,5 +8,5 @@
   "num_classes": null,
   "converted_from": "iic/speech_campplus_sv_zh_en_16k-common_advanced",
   "quantized": false,
-  "conversion_date": "2026-01-16T12:06:47.419878"
+  "conversion_date": "2026-01-16T12:19:25.841196"
 }

model.py

@@ -349,6 +349,63 @@ class CAMPPModelScopeV2(nn.Module):
 
         return embedding
 
+    def load_weights(self, file_or_weights, strict: bool = True):
+        """
+        Override load_weights to handle quantized weights with dequantization
+
+        Args:
+            file_or_weights: Path to .npz file or list of (name, array) tuples
+            strict: If True, all parameters must match exactly
+        """
+        # Load weights from file if needed
+        if isinstance(file_or_weights, str):
+            loaded_weights = mx.load(file_or_weights)
+        else:
+            loaded_weights = dict(file_or_weights)
+
+        # Dequantize weights that have scales and biases
+        dequantized_weights = {}
+        quantized_names = set()
+
+        for name, array in loaded_weights.items():
+            # Check if this is a quantized weight by looking for scales/biases with metadata
+            # Format: name:qSCALES_GS64_B4 or name:qBIASES_GS64_B4
+            if ':qSCALES_GS' in name or ':qBIASES_GS' in name:
+                # Skip, will be processed when we see the main weight
+                continue
+
+            # Check if this weight has quantization metadata
+            has_quantization = any(k.startswith(f"{name}:qSCALES_GS") for k in loaded_weights.keys())
+
+            if has_quantization:
+                # Find the scales key to extract group_size and bits
+                scales_key = next(k for k in loaded_weights.keys() if k.startswith(f"{name}:qSCALES_GS"))
+                # Parse: name:qSCALES_GS64_B4 -> extract GS64 and B4
+                import re
+                match = re.search(r'GS(\d+)_B(\d+)', scales_key)
+                if match:
+                    group_size = int(match.group(1))
+                    bits = int(match.group(2))
+
+                    # Get scales and biases
+                    biases_key = f"{name}:qBIASES_GS{group_size}_B{bits}"
+                    scales = loaded_weights[scales_key]
+                    biases = loaded_weights[biases_key]
+
+                    # Dequantize the weight
+                    dequantized = mx.dequantize(array, scales, biases, group_size=group_size, bits=bits)
+                    dequantized_weights[name] = dequantized
+                    quantized_names.add(name)
+                else:
+                    # Fallback: couldn't parse, keep original
+                    dequantized_weights[name] = array
+            else:
+                # Regular weight (not quantized)
+                dequantized_weights[name] = array
+
+        # Use the parent class load_weights with dequantized weights
+        super().load_weights(list(dequantized_weights.items()), strict=strict)
+
 
 def load_model(weights_path: str, config_path: Optional[str] = None) -> CAMPPModelScopeV2:
     """Load model from weights and config"""