Fix issues with quantization_config == None

src/llama_recipes/inference/model_utils.py

@@ -20,13 +20,17 @@ def load_model(model_name, quantization, use_fast_kernels, **kwargs):
         bnb_config = quant_config.create_bnb_config(quantization)
 
     print(f"use_fast_kernels{use_fast_kernels}")
+
+    kwargs = {}
+    if bnb_config:
+        kwargs["quantization_config"]=bnb_config,
+    kwargs["device_map"]="auto"
+    kwargs["low_cpu_mem_usage"]=True
+    kwargs["attn_implementation"]="sdpa" if use_fast_kernels else None
     model = AutoModelForCausalLM.from_pretrained(
         model_name,
         return_dict=True,
-        quantization_config=bnb_config,
-        device_map="auto",
-        low_cpu_mem_usage=True,
-        attn_implementation="sdpa" if use_fast_kernels else None,
+        **kwargs,
     )
     return model