Update README.md

README.md

@@ -1,19 +1,40 @@
-## How to use?
-### Specifically finetuned for bank queries , to understand weather user want to to trasaction or not.
+---
+language: en
+license: apache-2.0
+tags:
+  - text-classification
+  - banking
+  - intent-detection
+  - transformers
+library_name: transformers
+pipeline_tag: text-classification
+---
 
-hf_model = "pankaj1881/question-classification"
+# Question Classification Model for Bank Queries
 
-#### question classification pipeline 
-classifier = pipeline("text-classification", model=hf_model )
+This model is fine-tuned specifically for banking-related queries to classify whether a user intends to perform a **transaction** or not.
 
+## 🧠 Use Case
 
-#### prediction
-query = " your question or statement"
+Given a text input (a user question or statement), the model returns:
+- `"True"`: if the query is a **transaction-related question**
+- `"False"`: otherwise
 
-result = classifier(query) # return "True" if query === question ,  else "False"  # return "True" if query === question ,  else "False"
+---
 
-print(result)
+## 🔧 How to Use
+
+You can use this model directly with the Hugging Face `transformers` pipeline:
+
+```python
+from transformers import pipeline
 
+hf_model = "pankaj1881/question-classification"
+
+classifier = pipeline("text-classification", model=hf_model)
 
-## output 
-### [{'label': 'True', 'score': 0.8767889142036438}]
+query = "I want to transfer 500 dollars to my friend"
+result = classifier(query)
+
+print(result)
+# Output example: [{'label': 'True', 'score': 0.8767889142036438}]