Update README.md

README.md

@@ -35,18 +35,27 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-More information needed
+This is my first fine-tuning experiment using Hugging Face.
+Using distilBERT as a pretrained model, I trained a classifier for online banking queries.
+It could be useful for addressing tickets.
 
 ## Intended uses & limitations
 
-More information needed
+The model can be used on text classification. In particular is fine tuned on banking domain.
 
 ## Training and evaluation data
 
-More information needed
+The dataset used is [banking77](https://huggingface.co/datasets/banking77) 
 
 ## Training procedure
 
+```
+from transformers import pipeline
+
+pipe = pipeline("text-classification", model="nickprock/distilbert-base-uncased-banking77-classification")
+pipe("I can't pay by my credit card")
+```
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training: