Optimized and Quantized DistilBERT with a custom pipeline with handler.py

NOTE: Blog post coming soon

1. Specify the requirements by defining a requirements.txt file.
2. Implement the handler.py __init__ and __call__ methods. These methods are called by the Inference API. The __init__ method should load the model and preload the optimum model and tokenizers as well as the text-classification pipeline needed for inference. This is only called once. The __call__ method performs the actual inference. Make sure to follow the same input/output specifications defined in the template for the pipeline to work.