Update 1

Author: 1ssb

README.md

@@ -1,3 +1,48 @@
 # torchkan
 
-Under Development
+**Under Development**
+
+
+# TorchKAN: KAN Model Evaluation with PyTorch and CUDA
+
+This project demonstrates the training, validation, and quantization of the simplified KAN model using PyTorch, with CUDA acceleration for improved performance. The project builds the `torchkan` library to create and evaluate KAN models on the MNIST dataset, as a preliminary test.
+
+## Prerequisites
+
+Before you begin, ensure you have the following installed on your system:
+- Python (version 3.6 or higher)
+- CUDA Toolkit (corresponding to the CUDA version required by your PyTorch installation)
+- cuDNN (compatible with your installed CUDA Toolkit)
+
+## Installation (Tested on MacOS and Linux)
+
+### 1. Clone the Repository
+
+Start by cloning the repository containing the `torchkan` library and navigating into the project directory:
+
+```bash
+git clone https://github.com/1ssb/torchkan.git
+cd torchkan
+pip install -r requirements.txt
+```
+
+If not already installed:
+
+```bash
+export PATH=/usr/local/cuda/bin:$PATH
+export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
+```
+
+To run the MNIST training, make sure you configure wandb and run the script:
+
+```python
+python mnist.py
+```
+
+## Contact
+
+For questions contact me at Subhransu.Bhattacharjee@anu.edu.au
+
+## Contributions
+
+Contributions are welcome, please raise issues as required after commit Fin. This repository is still under development and testing. The code is licensed under the MIT License.