Update README.md

README.md

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 - token classification
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 # 🛰️ Spacika — Custom Named Entity Recognition Model
 
 **Spacika** is a powerful and lightweight Named Entity Recognition (NER) model, fine-tuned to extract meaningful entities like names, organizations, locations, and more from natural language text.
@@ -26,17 +28,9 @@ Created with precision and passion by **[Varnika](https://huggingface.co/Varnika
 ## ✨ Features
 
 - ✅ Fast and efficient NER tagging
-- 🧠 Transformer-based backbone (custom-trained with spaCy v3)
+- 🧠 Transformer-based backbone 
 - 📚 Trained on domain-specific and/or general English data
 - 🔖 Identifies entities like `PERSON`, `ORG`, `GPE`, `DATE`, `MONEY`, and more
 - 🌐 Easy to load, test, and integrate into any Python NLP workflow
 
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-
-## 🚀 How to Use
-
-### 🔧 Installation
-
-```bash
-pip install spacy
-python -m spacy download Varnikasiva/Spacika