fix typo

README.md

@@ -7,13 +7,14 @@ base_model:
 
 
 
+
 ---
 
 ## Model Details
 
-This model is an int2 model with group_size  64 and symmetric quantization of [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) generated by [intel/auto-round](https://github.com/intel/auto-round) algorithm.  Some layers are fallback to 4/16 bits. Refer to  Section "Generate the model" for more details of mixed bits setting.
+This model is an int2 model with group_size 64 and symmetric quantization of [deepseek-ai/DeepSeek-R1](https://huggingface.co/deepseek-ai/DeepSeek-R1) generated by [intel/auto-round](https://github.com/intel/auto-round) algorithm. We recommend using a mixed version [OPEA/DeepSeek-R1-int2-mixed-sym-inc](https://huggingface.co/OPEA/DeepSeek-R1-int2-mixed-sym-inc) for better accuracy
 
-Please follow the license of the original model. This model could **NOT** run on other severing frameworks. 
+Please follow the license of the original model.
 
 ## How To Use
 
@@ -240,7 +241,8 @@ model = AutoModelForCausalLM.from_pretrained(
     torch_dtype=torch.bfloat16,
     trust_remote_code=True,
     device_map="cpu",
-    quantization_config=quantization_config
+    quantization_config=quantization_config,
+    revision="080ef2d"
 )
 
 
@@ -416,7 +418,6 @@ model = AutoModelForCausalLM.from_pretrained(
     torch_dtype=torch.float16,
     trust_remote_code=True,
     device_map=device_map,
-    revision="080ef2d"
 )
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
@@ -504,7 +505,6 @@ from auto_round import AutoRound
 
 
 
-
 autoround = AutoRound(model=model, tokenizer=tokenizer, device_map=device_map, bits=2, group_size=64,
                       iters=1000, batch_size=4, seqlen=512, nsamples=512, enable_torch_compile=False,
                    )