model_inference.qmd

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title: Model Inference
order: 5
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# Model Inference

The `model_inference` pipeline is designed to handle the final stage of inference. It currently includes a single placeholder node for **predicting outputs**, which you can customize to implement your model-specific inference logic.

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## Key Features

- **Placeholder Node**: The pipeline includes a template node for predictions. This ensures a simple starting point for implementing your inference workflow.
- **Customizable**: You can add additional nodes or modify the existing one to include preprocessing, postprocessing, or any additional operations required for inference.

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## Implementation Tips

1. **Add Batch Processing**  
   If your inference involves multiple inputs, consider implementing batch processing to optimize performance.

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## Next Steps

To complete the inference pipeline:
1. Replace the placeholder node with your model-specific prediction logic.
2. Integrate the `model_inference` pipeline with the `inf_data_preprocessing` pipeline to create a seamless end-to-end workflow.