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.

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.

Implementation Tips

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

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.