feature: 🧾 Add telegram & fix image in Readme

README.md

@@ -1,16 +1,25 @@
 # CryptoHack-AI
+
 <div align="center">
   <br/>
-<img src="https://raw.githubusercontent.com/Chonete-Builders/CryptoHack-AI/main/CryptoStarkLogo.png" alt="CryptoHack-AI Small" width="200" />
+<img src="CryptoHackAI-web/public/CryptoStarkLogo.png" 
+alt="CryptoHack-AI Small" width="200" />
 </div>
 
 ## Overview
 
-CryptoHack-AI is an AI-powered assistant designed to help generate innovative ideas for cryptocurrency and AI projects. From brainstorming tokenomics and decentralized applications to identifying AI-based solutions for real-world problems, CryptoHack-AI ensures you have all the inspiration and guidance needed to kickstart your projects.  
+CryptoHack-AI is an AI-powered assistant designed to help generate innovative ideas for cryptocurrency and AI projects. From brainstorming tokenomics and decentralized applications to identifying AI-based solutions for real-world problems, CryptoHack-AI ensures you have all the inspiration and guidance needed to kickstart your projects.
 
 ---
 
+## Join our community
+
+[Discord](https://discord.gg/ZSyShWJmHB)
+
+[Telegram](https://t.me/+bDWJoAuVATg2YzQx)
+
 ## Technologies Used
+
 - **Model**: [CryptoHack-AI Model](https://huggingface.co/jsandinoDev/CryptoHack-AI_gpt2)
 - **Training Environment**: Google Colab
 - **Database**: Supabase with PostgreSQL
@@ -21,48 +30,55 @@ CryptoHack-AI is an AI-powered assistant designed to help generate innovative id
 
 ## How It Works
 
-## **Data Collection** 📊  
-The data used for CryptoHack-AI was gathered from diverse online sources such as:  
-- Blockchain and cryptocurrency whitepapers  
-- AI and tech innovation blogs  
-- Research papers and forums  
+## **Data Collection** 📊
+
+The data used for CryptoHack-AI was gathered from diverse online sources such as:
+
+- Blockchain and cryptocurrency whitepapers
+- AI and tech innovation blogs
+- Research papers and forums
 
 This foundational dataset provides a starting point for generating creative ideas, and future iterations will incorporate larger datasets for even broader coverage and better suggestions.
 
 ---
 
-## **Model Training** 🧠  
+## **Model Training** 🧠
+
 The AI model behind CryptoHack-AI was built using **GPT-2** as the base model, fine-tuned for idea generation in the crypto and AI domains.
 
-### Training Process:  
-1. **Platform**: The training was conducted on **Google Colab**, utilizing its GPU acceleration to efficiently fine-tune the model.  
-2. **Dataset Preparation**: The collected data was cleaned, structured, and formatted to suit GPT-2's input requirements.  
-3. **Fine-Tuning**: Using Hugging Face’s Transformers library, the model was customized to focus on generating actionable ideas and strategies for crypto and AI projects.  
+### Training Process:
+
+1. **Platform**: The training was conducted on **Google Colab**, utilizing its GPU acceleration to efficiently fine-tune the model.
+2. **Dataset Preparation**: The collected data was cleaned, structured, and formatted to suit GPT-2's input requirements.
+3. **Fine-Tuning**: Using Hugging Face’s Transformers library, the model was customized to focus on generating actionable ideas and strategies for crypto and AI projects.
 4. **Evaluation**: Initial results are promising, but there’s room to refine the dataset and enhance the model for better context understanding.
 
 ---
 
-## **Deployment** 🚀  
-The trained model was deployed using:  
-- **Hugging Face Spaces**: Hosting the model on Hugging Face Spaces makes it accessible via API for seamless integration into the application.  
-- **Vercel**: The app frontend is deployed on **Vercel**, ensuring optimal performance and scalability for end-users.  
+## **Deployment** 🚀
+
+The trained model was deployed using:
+
+- **Hugging Face Spaces**: Hosting the model on Hugging Face Spaces makes it accessible via API for seamless integration into the application.
+- **Vercel**: The app frontend is deployed on **Vercel**, ensuring optimal performance and scalability for end-users.
 
 The deployment combines the AI model with an intuitive UI, enabling users to quickly interact and generate ideas in real-time.
 
 ---
 
-## **Integration** 🗄️  
-**Supabase** and **PostgreSQL** were utilized as the backend infrastructure to handle data storage and management:  
+## **Integration** 🗄️
 
-- **Supabase**:  
-  - Provides a backend-as-a-service (BaaS) platform.  
-  - Enables real-time data handling and user authentication.  
+**Supabase** and **PostgreSQL** were utilized as the backend infrastructure to handle data storage and management:
 
-- **PostgreSQL**:  
-  - Stores user queries, project ideas, and preferences for future reference.  
-  - Ensures secure and efficient data management for personalized experiences.  
+- **Supabase**:
+
+  - Provides a backend-as-a-service (BaaS) platform.
+  - Enables real-time data handling and user authentication.
+
+- **PostgreSQL**:
+  - Stores user queries, project ideas, and preferences for future reference.
+  - Ensures secure and efficient data management for personalized experiences.
 
 Together, these technologies provide a robust and reliable foundation for CryptoHack-AI's functionality.
 
 ---
-