Fitting a Multi-Regression Model in Python

Question

I am very new to coding and am in the learning phase. I am using numpy & pandas. I have come across an exercise that needs more help understanding it.

The Data includes 3 predictors ('x1' , 'x2' , 'x3') and one target ('Target').

The question I am stuck at;

How do you create different multi-predictor models?

I need to create a list of lists of all unique predictor combinations to fit the curve.

# Create a list of lists of all unique predictor combinations to fit the curve
cols = df.drop(['Target'],axis=1)

# Loop over all the predictor combinations 
for i in cols:
    x = cols[i]
    y = df['Target']