Update README.md

README.md

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 ## Dataset Overview
 This repository contains a synthetic dataset generated for the SmartFit AI project. The dataset consists of 10,000 user profiles designed to train a machine learning model for personalized workout recommendations. It simulates various biological and preference-based factors including age, gender, weight, height, fitness goals, equipment availability, and injuries.
 
+The data is stored in **Parquet format** (Hugging Face native) for high efficiency and fast loading.
+
 ## Repository Contents
 
-* **smart_fit_dataset.csv**: The primary dataset containing the raw tabular data used for training the model.
-* **fitness_embeddings.npy**: Pre-computed vector embeddings of the user profiles.
-* **Copy_of_Final_Project.ipynb**: The complete Jupyter Notebook containing data generation, training, and evaluation logic.
-* **imp1.png**: Visualization of the Exploratory Data Analysis (EDA).
-* **imp3.png**: Visualization of the Embeddings Analysis (PCA Clustering).
+* **fitness_embeddings.npy (1)**: Pre-computed vector embeddings of the user profiles (generated via Sentence Transformer).
+* **imp88.png**: Visualization of the Exploratory Data Analysis (EDA).
+* **imp888.png**: Visualization of the Embeddings Analysis (PCA Clustering).
 
 ## Exploratory Data Analysis (EDA)
 The visualization below demonstrates the distribution and characteristics of the synthetic data. This analysis ensures the dataset is balanced across different categories and logically consistent regarding injuries and recommended plans.