[USER (data scientist)]: I've got this dataset called "high_credit_long_duration" and I need to find clients with multiple existing credits and high installment commitments. We also assume that `high` installment commitments are those above the `median` value of the 'installment_commitment' column. Can you help me out? Please generate the code with the output in dataframe type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
import pickle
from decision_company import read_csv_file, calculate_median, filter_by_condition, create_condition, logical_and, fetch_index, convert_to_list, fetch_column

# Load the dataset  
credit_customers = read_csv_file("credit_customers.csv")   
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]
</code1>
# YOUR SOLUTION END

print(f"multiple_credits_high_commitment: {multiple_credits_high_commitment}")  

# save data
pickle.dump(multiple_credits_high_commitment, open("./pred_result/multiple_credits_high_commitment.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure! You can use the following code to find clients with multiple existing credits and high installment commitments:

# MY SOLUTION BEGIN:
