Update README.md

README.md

@@ -7,26 +7,24 @@ language:
 - it
 ---
 
-# Mistral-RAG
-
-## Model Details
+## Mistral-RAG
 - **Model Name:** Mistral-RAG
 - **Base Model:** Mistral-Ita-7b
 - **Specialization:** Question and Answer Tasks
 
-## Overview
+### Overview
 Mistral-RAG is a refined fine-tuning of the Mistral-Ita-7b model, engineered specifically to enhance question and answer tasks. It features a unique dual-response capability, offering both generative and extractive modes to cater to a wide range of informational needs.
 
-## Capabilities
+### Capabilities
 
-### Generative Mode
+#### Generative Mode
 - **Description:** The generative mode is designed for scenarios that require complex, synthesized responses. This mode integrates information from multiple sources and provides expanded explanations.
 - **Ideal Use Cases:** 
   - Educational purposes
   - Advisory services
   - Creative scenarios where depth and detailed understanding are crucial
 
-### Extractive Mode
+#### Extractive Mode
 - **Description:** The extractive mode focuses on speed and precision. It delivers direct and concise answers by extracting specific data from texts.
 - **Ideal Use Cases:**
   - Factual queries in research
@@ -34,7 +32,7 @@ Mistral-RAG is a refined fine-tuning of the Mistral-Ita-7b model, engineered spe
   - Professional environments where accuracy and direct evidence are necessary
 
 
-## How to Use
+### How to Use
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer