Update README.md

README.md

@@ -1,6 +1,6 @@
-# LangPWT
+# Leap-0
 
-This repository contains the implementation of a lightweight, modified version of the GPT architecture **LangPWT** trained from scratch using FineWeb-Edu, an open-source dataset. The project demonstrates the design, training, and optimization of a custom natural language model on local hardware.  
+This repository contains the implementation of a lightweight, modified version of the GPT architecture **Leap-0** trained from scratch using FineWeb-Edu, an open-source dataset. The project demonstrates the design, training, and optimization of a custom natural language model on local hardware.  
 
 ## Features  
 - **Custom GPT Architecture**: A miniaturized version of the GPT model tailored for efficient training on limited hardware.  
@@ -10,7 +10,7 @@ This repository contains the implementation of a lightweight, modified version o
 
 <div align="center">
   <img src="LLM.drawio.png" alt="Description of the image" width="300">
-   <p><strong>Figure 1: Architecture of LangPWT</p>
+   <p><strong>Figure 1: Architecture of Leap</p>
 </div>
 
 ## Implementation Details  
@@ -19,7 +19,7 @@ This repository contains the implementation of a lightweight, modified version o
    - Incorporates modifications to parameter scaling to suit resource-constrained environments.  
 
 2. **Training**  
-   - Training executed locally on NVIDIA GeForce RTX 3050 (Laptop) 4GB GPU, leveraging PyTorch.
+   - Training executed locally on NVIDIA GeForce RTX 4500 ada 24GB GPU, leveraging PyTorch.
     
 3. **Testing**
    - A simple Streamlit UI created for testing generation capability of the model.
@@ -66,26 +66,4 @@ This repository contains the implementation of a lightweight, modified version o
 - Dependencies listed in `requirements.txt`
 - **Note**: Different OS support different versions of PyTorch/Tensorflow to use CUDA (local GPU). Install only after verifying for your OS. 
 
-## Usage  
-1. Clone the repository:  
-  ```bash
-  git clone https://github.com/pulkundwar29/LangPWT
-  cd LangPWT
-  ```
-2. Create and activate a virtual environment:
-  ```bash
-  venv env
-  env\scripts\activate
-  ```
-3. Install dependencies:
-  ```bash
-  pip install -r requirements.txt
-  ```
-4. Run the training file **trainpwt.py**
-5. Run the streamlit file: **trial_pwt.py** 
-6. Enter your prompt and hit the Generate button.
 
-<div align="center">
-  <img src="ex1.png" alt="example text">
-   <p><strong>Figure 2: Example of Text Generated using LangPWT</p>
-</div>