Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- text-classification
+language:
+- it
+size_categories:
+- n<1K
+---
+
+# Italian Running Shoes Dataset (Multimodal)
+
+This dataset contains a collection of **running shoe products** specifically curated from the Italian market. It is designed for tasks such as Computer Vision (Image Classification), Natural Language Processing (NLP) in Italian, and E-commerce recommendation systems.
+
+## 📂 Dataset Structure
+
+The dataset consists of a central metadata file and a folder containing product images.
+
+* `images/`: Directory containing `.jpg` images of the shoes.
+* `shoes_metadata.csv`: A CSV file containing product details in Italian.
+
+## 📊 Data Dictionary
+
+The `shoes_metadata.csv` file uses a comma-separated format with the following columns:
+
+| Column | Description | Example |
+| --- | --- | --- |
+| **brand** | The manufacturer of the shoe. | `Adidas` |
+| **nome** | The product name and colorway. | `Runfalcon 5 Nero` |
+| **descrizione** | A detailed description in **Italian**, often including discounts. | `Adidas Scarpa da Running Donna...` |
+| **prezzo** | The price in Euro (€). | `60,00` |
+| **immagine** | The filename of the corresponding image in the `/images` folder. | `ADIDIE8826_VAR_01_3480.jpg` |
+
+## 📝 Sample Data
+
+```csv
+"brand","nome","descrizione","prezzo","immagine"
+"Adidas","Runfalcon 5 Nero","Adidas Scarpa da Running Donna Runfalcon 5 Nero","60,00","ADIDIE8826_VAR_01_3480.jpg"
+"Adidas","Adistar 3 Blu Fucsia","Adidas Scarpa da Running Donna Adistar 3 Blu Fucsia Sconto 10%","126,00","ADIDJI1230_VAR_01_38b8.jpg"
+
+```
+
+## 🚀 Use Cases
+
+1. **Image Classification:** Training models to recognize shoe brands or specific models.
+2. **Price Prediction:** Analyzing the correlation between product descriptions and their retail price.
+3. **Italian NLP:** Fine-tuning LLMs or NER (Named Entity Recognition) models to extract features (gender, color, discount) from Italian commercial text.
+
+## 🛠 How to Use with Python
+
+```python
+import pandas as pd
+
+# Load the metadata
+df = pd.read_csv('shoes_metadata.csv')
+
+# Display the first few rows
+print(df.head())
+
+```