save non-transformer params separately

cli/quantize_for_cpu.py

@@ -47,3 +47,7 @@ if __name__ == "__main__":
             layer_fp32, {torch.nn.Linear: qconfig}, dtype=torch.qint8, inplace=True
         )
         torch.save(layer_quantized.state_dict(), os.path.join(args.output_path, f"block_{i}_qint8.pth"))
+
+    model.transformer.h = torch.nn.ModuleList()
+    torch.save(model.state_dict(), os.path.join(args.output_path, f"client.pth"))
+