int4 => int8 handler with bitwidth =4

quantize.py

@@ -481,6 +481,7 @@ def __init__(self, mod, group_size):
     def create_quantized_state_dict(self):
         from hqq.core.quantize import Quantizer  # TODO maybe torchao
 
+
         for m in self.mod.modules():
             for name, child in m.named_children():
                 if isinstance(child, torch.nn.Linear):
@@ -495,11 +496,16 @@ def create_quantized_state_dict(self):
                         )
                     )
 
-        return WeightOnlyInt4QuantHandler(self.mod, self.groupsize).create_quantized_state_dict()
+        # we use Int4 packaged in an int8 for now, packing to follow
+        # return WeightOnlyInt4QuantHandler(self.mod, self.groupsize).create_quantized_state_dict()
+        return WeightOnlyInt8QuantHandler(self.mod, bitwidth=4, self.groupsize).create_quantized_state_dict()
 
     def _convert_for_runtime(self):
-        return WeightOnlyInt4GPTQQuantHandler(self.mod, self.groupsize).convert_for_runtime(use_cuda=True)
-
+        # we use Int4 packaged in an int8 for now, packing to follow
+        # ALSO: all code must work for CPU, CUDA, MPS
+        # return WeightOnlyInt4GPTQQuantHandler(self.mod, self.groupsize).convert_for_runtime(use_cuda=True)
+        return WeightOnlyInt4GPTQQuantHandler(self.mod, bitwidth=4, self.groupsize).convert_for_runtime()
+
     def quantized_model(self) -> nn.Module:
         model_updated_state_dict = self.create_quantized_state_dict()
         self.convert_for_runtime()