Error when deploying the model

Using Streamlit
1

I trained a xgboost model in kaggle, Now I want to use that model for deployment. During deployment it is showing error as

NumExpr defaulting to 8 threads.

and it stops.
Here is the code when user presses submit button.

predict=st.button('submit')
model_path='R:/home-ste-deployment/xgb.pkl'
if predict:
    model_data=data.values
    model_data=scaler.transform(model_data)
    with open(model_path,'rb') as f:
        model=pickle.load(f)
    predictions=model.predict(model_data)
    st.write(predictions)

I am having same version of xgboost on my system which I used for training purpose.
If I simply run the code as below I am getting output, but not when using in streamlit code.

with open(model_path,'rb') as f:
        model=pickle.load(f)
predictions=model.predict(np.zeros((1,451)))
print(predictions)
[1]
2

Where are you trying to deploy this model, Streamlit sharing?

3

I got the solution. Instead of using pickle if I use xgb.save_model and load model by xgb.load_model I am not getting any error. Thanks for replying.