Update README.md

README.md

@@ -5,7 +5,7 @@ Current protein language models (PLMs) learn protein representations mainly base
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/62f0a673f0d40f6aae296b4a/o4F5-Cm-gGdHPpX5rPVKx.png)
 
 ## Example
-This example shows how to use ProtST on zero-shot classification task.
+The following script shows how to run ProtST with [optimum-intel](https://github.com/huggingface/optimum-intel) optimization on zero-shot classification task.
 ```python
 import logging
 import functools
@@ -83,6 +83,10 @@ if __name__ == "__main__":
     
     protst_model = AutoModel.from_pretrained("Jiqing/ProtST-esm1b", trust_remote_code=True, torch_dtype=torch.bfloat16).to(device)
     protein_model = protst_model.protein_model
+    + import intel_extension_for_pytorch as ipex
+    + from optimum.intel.generation.modeling import jit_trace
+    + protein_model = ipex.optimize(protein_model, dtype=torch.bfloat16, inplace=True)
+    + protein_model = jit_trace(protein_model, "sequence-classification")
     text_model = protst_model.text_model
     logit_scale = protst_model.logit_scale
     logit_scale.requires_grad = False