diff --git a/neural_speed/__init__.py b/neural_speed/__init__.py
index afc1a6100..a850c6097 100644
--- a/neural_speed/__init__.py
+++ b/neural_speed/__init__.py
@@ -83,7 +83,7 @@ def get_model_type(model_config):
             model_type = "chatglm2"
         return model_type
 
-    def init(self, model_name, use_quant=True, use_gptq=False, use_awq=False,
+    def init(self, model_name, use_quant=True, use_gptq=False, use_awq=False, use_autoround=False,
             weight_dtype="int4", alg="sym", group_size=32,
             scale_dtype="fp32", compute_dtype="int8", use_ggml=False):
         self.config = AutoConfig.from_pretrained(model_name, trust_remote_code=True)
@@ -107,6 +107,8 @@ def init(self, model_name, use_quant=True, use_gptq=False, use_awq=False,
             quant_desc = "gptq"
         if use_awq:
             quant_desc = "awq"
+        if use_awq:
+            quant_desc = "autoround"
         quant_bin = "{}/ne_{}_q_{}.bin".format(output_path, model_type, quant_desc)
 
         if not use_quant:
@@ -119,8 +121,8 @@ def init(self, model_name, use_quant=True, use_gptq=False, use_awq=False,
                   format(self.bin_file))
             return
 
-        if use_gptq or use_awq:
-            convert_model(model_name, quant_bin, "f32")
+        if use_gptq or use_awq or use_autoround:
+            convert_model(model_name, quant_bin, use_quantized_model=True)
             return
         
         if not os.path.exists(fp32_bin):
diff --git a/neural_speed/convert/__init__.py b/neural_speed/convert/__init__.py
index da272ce32..9f063a5ec 100644
--- a/neural_speed/convert/__init__.py
+++ b/neural_speed/convert/__init__.py
@@ -22,12 +22,11 @@
 model_maps = {"gpt_neox": "gptneox", "gpt_bigcode": "starcoder", "whisper": "whisper"}
 
 
-def convert_model(model, outfile, outtype, whisper_repo_path=None):
+def convert_model(model, outfile, outtype="f32", whisper_repo_path=None, use_quantized_model=False):
     config = AutoConfig.from_pretrained(model, trust_remote_code=True)
     model_type = model_maps.get(config.model_type, config.model_type)
 
-    quantized_model = 'gptq' in str(model).lower() or 'awq' in str(model).lower()
-    if quantized_model:
+    if use_quantized_model:
         path = Path(Path(__file__).parent.absolute(), "convert_quantized_{}.py".format(model_type))
     else:
         path = Path(Path(__file__).parent.absolute(), "convert_{}.py".format(model_type))