Update README.md

README.md

@@ -4,4 +4,19 @@ tags:
 library_name: generic
 ---
 
-# Optimized and Quantized DistilBERT with a custom pipeline.py
+# Optimized and Quantized DistilBERT with a custom pipeline.py
+
+> NOTE: Blog post coming soon
+
+This is a template repository for Text Classification using Optimum and onnxruntime to support generic inference with Hugging Face Hub generic Inference API. There are two required steps:
+
+1. Specify the requirements by defining a `requirements.txt` file.
+2. Implement the `pipeline.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.
+
+add 
+```
+library_name: generic
+```
+to the readme.
+
+_note: the `generic` community image currently only support `inputs` as parameter and no parameter._