Add README content with instructions and examples

Included usage guide, supported languages, and placeholder examples for users.

README.md

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 license: apache-2.0
 short_description: Multilingual NER app using Gradio.
 ---
+# 🌍 Multilingual Named Entity Recognition (NER) App — Hugging Face Version
+
+A robust and multilingual Named Entity Recognition (NER) app powered by **Gradio** and Hugging Face Transformers. It extracts entities such as names, organizations, and locations from user input across multiple languages.
+
+## 🧠 About the Model
+- **Pipeline:** `ner`
+- **Model:** `Davlan/xlm-roberta-base-ner-hrl`
+- **Framework:** Hugging Face Transformers
+- **Task:** Named Entity Recognition (NER) in multiple languages
+
+## 💡 Features
+- Supports multilingual input (English, Spanish, German, French, etc.)
+- Extracts key entities like names, organizations, and locations
+- Real-time inference with clear visual output
+- Hosted on Hugging Face Spaces
+
+## ⚙️ Instructions for Users
+
+> This app identifies entities like names, organizations, and places in your sentence.
+> 
+> ✅ Works best with supported languages such as **English**, **Spanish**, **French**, **German**, **Dutch**, **Chinese**, **Hindi**, and more.
+> 
+> ⚠️ Avoid using overly long or grammatically broken inputs.
+> 
+> ❌ Less effective for **Japanese**, and unsupported languages or mixed scripts.
+
+### 📌 Example Inputs
+
+**English:**  
+`Barack Obama was born in Hawaii and served as the 44th president of the United States.`
+
+**Spanish:**  
+`Lionel Messi nació en Rosario y juega para la selección de Argentina.`
+
+**French:**  
+`Emmanuel Macron est le président de la République française.`
+
+**German:**  
+`Angela Merkel war die Bundeskanzlerin von Deutschland.`
+
+---
+
+## 🚀 How to Run Locally
+Install the required packages:
+```bash
+pip install -r requirements.txt
+```
+Then run the app:
+```bash
+python app.py
+```
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference