Update README.md

README.md

@@ -1,16 +1,149 @@
+---
+base_model: unsloth/deepseek-r1-distill-qwen-14b-unsloth-bnb-4bit
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen2
+- trl
+- ai
+- finetune
+license: apache-2.0
+language:
+- en
+---
+
+
+# CyberBrain_Model
+<p align="center">
+   <img src="https://capsule-render.vercel.app/api?type=waving&height=120&color=244b6c&text=Cyper%20Brain&section=header&textBg=false&animation=twinkling&fontColor=a5241b&strokeWidth=0&rotate=0&reversal=false" style="width:100%;">
+</p>
+CyberBrain_Model is an advanced AI project designed for fine-tuning the model `unsloth/DeepSeek-R1-Distill-Qwen-14B` specifically for cyber security tasks. This repository provides tools and scripts for training and fine-tuning large language models efficiently using minimal hardware resources. The goal is to adapt the model for ethical cyber security applications, making it efficient even on devices with limited computational power, whether you have a low-end CPU or a GPU with limited VRAM.
+
+In this project, we use technical content extracted from various cyber security sources as our primary training data. The raw text is processed into instruction-response pairs tailored for fine-tuning the model on cyber security scenarios. You can access the training data [here](./DataSet).
+
+![AI Training](assest/ai.jpg)
+
+## 📦 Project Structure
+
+```
+assest/                         # Assets, images, and other media files
+Configure_Training_Arguments.py  # Script for configuring training arguments
+DataSet/                         # Directory containing dataset files
+Load_DataSet.py                  # Script to load the dataset
+LoRA_Configuration.py            # Script for LoRA configuration
+map.md                           # Documentation about mapping
+Model_Loading_with_Unsloth.py    # Script to load the model using Unsloth
+README.md                        # This file
+requirements.txt                 # Required dependencies for the project
+Table-Ways.md                    # Documentation about table ways
+Train_Start.py                   # Script to start training the model
+```
+
+## 🚀 Installation
+
+### 1. Clone the Repository
+
+```bash
+git clone https://github.com/YourUsername/CyberBrain_Model.git
+cd CyberBrain_Model
+```
+
+### 2. Set Up the Environment
+
+Create a new virtual environment (Python 3.11 is recommended):
+
+```bash
+python -m venv .env
+# Activate the environment:
+# On Linux/Mac:
+source .env/bin/activate
+# On Windows:
+.env\Scripts\activate
+```
+
+### 3. Install Required Dependencies
+
+```bash
+pip install --upgrade pip
+pip install -r requirements.txt
+pip install torch==2.5.1+cu118 --index-url https://download.pytorch.org/whl/cu118
+pip install torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+```
+
+## 🤖 Running the Project
+
+- **Model Loading:** Run `Model_Loading_with_Unsloth.py` to load the model.
+- **Training:** Run `Train_Start.py` to start the fine-tuning process.
+- **Configurations:** Review `LoRA_Configuration.py` and `Configure_Training_Arguments.py` for training settings.
+
+## 📄 Additional Documentation
+
+Refer to the following files for more details:
+- `map.md`
+- `Table-Ways.md`
+
 ---
-base_model: unsloth/deepseek-r1-distill-qwen-14b-unsloth-bnb-4bit
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- qwen2
-- trl
-license: apache-2.0
-language:
-- en
+
+## 🚀 Quick Start on Google Colab
+
+To quickly run CyberBrain_Model on Google Colab, follow these steps:
+
+1. **Open a New Colab Notebook**  
+   Click [here](https://colab.new/) to open a new Colab notebook in your browser.
+
+2. **Clone the Repository**  
+   In your Colab notebook, run:
+   ```bash
+   !git clone https://github.com/YourUsername/CyberBrain_Model.git
+   %cd CyberBrain_Model
+   ```
+
+3. **Install Dependencies**  
+   Install the required packages by running:
+   ```bash
+   !pip install --upgrade pip
+   !pip install -r requirements.txt
+   !pip install torch==2.5.1+cu118 --index-url https://download.pytorch.org/whl/cu118
+   !pip install torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+   ```
+
+4. **Open and Run `main.ipynb`**  
+   Open the `main.ipynb` notebook in Colab. This notebook provides a step-by-step guide to:
+   - Load the dataset from the `DataSet` directory.
+   - Load the model using `Model_Loading_with_Unsloth.py`.
+   - Configure training arguments via `Configure_Training_Arguments.py`.
+   - Start training using `Train_Start.py`.
+   - Evaluate the model and monitor training progress.
+
 ---
 
+## License
+
+This project is licensed under the MIT License – see the [LICENSE](LICENSE) file for details.
+
+## Contact
+
+For questions or contributions, feel free to open an issue or contact us directly through GitHub.
+
+- Portfolio: [peteradel.netlify.app](https://peteradel.netlify.app)
+- LinkedIn: [linkedin.com/in/1peteradel](https://linkedin.com/in/1peteradel)
+
+## ⭐ Give a Star
+
+If you find this project useful or interesting, please give it a star! Your support helps improve the project and motivates further development.
+
+![AI Training](https://media0.giphy.com/media/v1.Y2lkPTc5MGI3NjExcXNhdWQzZWM0NzB6ZzRxcHZvdmxmMHJ3OWIwZ3RnZDY1dGJjZ3MxaSZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/H1eVHxFk781UxUNMul/giphy.gif)
+
+---
+
+🤍 Thank you for checking out **CyberBrain_Model**! Happy training!
+
+<p align="center">
+  <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&height=65&section=footer"/>
+</p>
+
+---
 # Uploaded  model
 
 - **Developed by:** PeterAdel
@@ -19,4 +152,4 @@ language:
 
 This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)