Update README.md

README.md

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----
-title: Stock Price Forecasting
-emoji: 📈
-colorFrom: blue
-colorTo: green
-sdk: gradio
-sdk_version: 4.16.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-# Stock Price Forecasting App
-
-This application uses three different models (ARIMA, Prophet, and LSTM) to forecast stock prices.
-
-## Features
-- Real-time stock data fetching from Yahoo Finance
-- Multiple forecasting models
-- Interactive visualizations
-- Customizable forecast periods
-
-## Models
-1. **ARIMA** - Traditional statistical model
-2. **Prophet** - Facebook's time series forecasting
-3. **LSTM** - Deep learning neural network
-
-## Usage
-1. Enter a stock ticker symbol (e.g., AAPL, GOOGL)
-2. Select forecast period (1-90 days)
-3. Choose which model(s) to use
-4. Click "Generate Forecast"
-
+---
+title: DataSynthis_ML_JobTask
+emoji: 📈
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 5.49.0
+app_file: app.py
+pinned: false
+license: mit
+allow_internet: true
+---
+
+# Stock Price Forecasting App
+
+This application uses three different models (ARIMA, Prophet, and LSTM) to forecast stock prices.
+
+## Features
+- Real-time stock data fetching from Yahoo Finance
+- Multiple forecasting models
+- Interactive visualizations
+- Customizable forecast periods
+
+## Models
+1. **ARIMA** - Traditional statistical model
+2. **Prophet** - Facebook's time series forecasting
+3. **LSTM** - Deep learning neural network
+
+## Usage
+1. Enter a stock ticker symbol (e.g., AAPL, GOOGL)
+2. Select forecast period (1-90 days)
+3. Choose which model(s) to use
+4. Click "Generate Forecast"
+
 ⚠️ **Disclaimer**: For educational purposes only. Not financial advice.