Update README

README.md

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 license: mit
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 # ML Assignment 3 – Maha Qaiser
 Dataset: California Housing from sklearn.datasets
-Repository: Contains the trained model for ML Assignment 3
 
 ## File Description
-- `best_model.joblib`: Mini-Batch Linear Regression model trained on the California Housing dataset
+- `best_model.joblib`: Mini-Batch Linear Regression model
+- `scaler.joblib`: StandardScaler object to preprocess input features
+- `inference.py`: Script to load the model + scaler and run predictions with user input
+
+## Model Overview
+- **Model Type:** Mini-Batch Linear Regression
+- **Features Used:**
+  - Avg. Rooms
+  - Avg. Bedrooms
+  - Population
+  - Household
+  - Median Income
+  - Latitude
+  - Longitude
+  - Housing Median Age
+- **Regularization:** L2 (Ridge)
+- **Early Stopping:** Applied during training
+
+## How to Run Inference
+### 1. Clone the repository or download the files:
+```bash
+git clone https://huggingface.co/mahaqj/ml_assignment_3
+cd ml_assignment_3
+```
+### 2. Install dependencies:
+```bash
+pip install joblib numpy scikit-learn huggingface_hub
+```
+### 3. Run the script:
+```bash
+python inference.py
+```
 
-## How to Use
+You’ll be prompted to enter the following features:
+- Avg. Rooms
+- Avg. Bedrooms
+- Population
+- Household
+- Median Income
+- Latitude
+- Longitude
+- Housing Median Age
+The model will return the predicted housing value.
+
+## Loading the Model in Python
 ```python
+from huggingface_hub import hf_hub_download
 import joblib
-model = joblib.load("best_model.joblib")
-predictions = model.predict(X_test)
+
+model_path = hf_hub_download(repo_id="mahaqj/ml_assignment_3", filename="best_model.joblib")
+scaler_path = hf_hub_download(repo_id="mahaqj/ml_assignment_3", filename="scaler.joblib")
+
+model = joblib.load(model_path)
+scaler = joblib.load(scaler_path)
+```