Update README.md

README.md

@@ -5,4 +5,54 @@ language:
 base_model:
 - dslim/distilbert-NER
 pipeline_tag: token-classification
----
+tags:
+- transport
+- bus
+---
+# 🚍 MyBusModel: A Custom NER Model for Public Transport Queries
+
+BusRouteNER is a lightweight, rule-enhanced Named Entity Recognition (NER) model fine-tuned for identifying **bus numbers** and **stops/locations** in natural language queries related to public transportation in West Bengal, India.
+
+---
+
+## ✨ What does this model do?
+
+This model is trained to extract two key entity types from user queries:
+
+- `BUS_NUMBER`: Recognizes bus numbers like `12C/1`, `S-12`, `12B`, etc.
+- `LOCATION`: Identifies source and destination locations such as `Howrah`, `Barrackpore`, `Santragachi`, etc.
+
+It also filters out irrelevant **noise words** to give a clean and accurate entity list that can be used in downstream logic such as search, recommendations, or route-finding.
+
+---
+
+## 🔍 Example
+
+**Input Query:**
+
+`I want to go from Santragachi to Barrackpore, can I take 12C/1 or S-12?`
+
+
+**Model Output:**
+
+`Santragachi LOCATION`
+
+`Barrackpore LOCATION`
+
+`12C/1 BUS_NUMBER`
+
+`S-12 BUS_NUMBER`
+
+
+---
+
+## 🧠 How it works
+
+- Built using **spaCy** (`en_core_web_sm`) and extended with `EntityRuler` for custom NER logic.
+- Bus numbers and stop names are sourced from curated CSV datasets.
+- Custom regex patterns identify bus numbers with formats like `12C/1`, `S-12`, etc.
+- Noise words like *I, want, take, can, should* are excluded from final entity extraction.
+
+---
+
+## 🛠 Usage