[USER (data scientist)]: Now that the data is preprocessed, I want to determine the optimal number of clusters using the silhouette score. Can you help me with that? Please generate a plot displaying the silhouette scores for different numbers of clusters in the KMeans clustering of the dataset.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd 
from sklearn.cluster import KMeans 
from sklearn.metrics import silhouette_score 
import matplotlib.pyplot as plt
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
<code1>
[COMPLETE YOUR CODE]
</code1>
# YOUR SOLUTION END

# Plot silhouette scores 
plt.figure(figsize=(10, 6)) 

# YOUR SOLUTION BEGIN:
<code2>
[COMPLETE YOUR CODE]
</code2>
# YOUR SOLUTION END

plt.savefig('pred_result/Silhouette_Scores.png') 
plt.show()

---END CODE TEMPLATE---

[YOU (AI assistant)]: Sure, I'll calculate the silhouette scores for different numbers of clusters and plot the results. Here's the code for that:
'''
import pandas as pd 
from sklearn.cluster import KMeans 
from sklearn.metrics import silhouette_score 
import matplotlib.pyplot as plt
 
# Load the dataset 
credit_customers = pd.read_csv("credit_customers.csv") 
 
# YOUR SOLUTION BEGIN:
