Here is an ML training script that saved its model binaries as files:

```python
{{  training_code }}
```

Your task is to generate Python code to instantiate the ML model for inference, using the artifacts created
by the training script above. The model loading should take place in the __init__ method of the PredictorImplementation
class in the following template script:

```python
{{ predictor_template }}
```

Your code should:
1. Add any required imports to the script (at the top of the file)
2. Load all model files (models, preprocessors, etc.) that were saved during training
3. Initialize any required variables or configurations inside __init__
4. Only use the libraries and frameworks that were used in the model training code

Only add the model instantiation code to __init__. Do not add prediction, input processing or output postprocessing
code to the script. Do not change the contract of the PredictorImplementation class, or the signature of its methods.
Do not remove the helper comments, except for those related to the model loading you are implementing. Return the full
inference script, with the model loading code now added to __init__.