Update README.md

README.md

@@ -6,8 +6,35 @@ datasets:
 language:
 - it
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+
+# Mistral-RAG
+
+## Model Details
+- **Model Name:** Mistral-RAG
+- **Base Model:** Mistral-Ita-7b
+- **Specialization:** Question and Answer Tasks
+
+## 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
+
+### 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
+- **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
+  - Legal contexts
+  - Professional environments where accuracy and direct evidence are necessary
+
+
 ## How to Use
-How to utilize my Mistral for Italian text generation
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer