This project is a Docker-based environment for deep learning and data science, utilizing NVIDIA CUDA and PyTorch.
It's optimized to be able to run on a paperspace environment.

Overview

This project provides a pre-configured Docker environment for deep learning and data science tasks, including:

• NVIDIA CUDA 12.4.0
• PyTorch 2.5.0
• JupyterLab and iPyWidgets for interactive development

Requirements

• Docker installed on your system

Usage

1. Build the Docker image by running docker build -t my-image . in the project directory.
2. Run the Docker container using docker run -it my-image.
3. To start JupyterLab, run jupyter lab --allow-root --ip=0.0.0.0 --port=8888 inside the container.
4. Access JupyterLab by navigating to http://localhost:8888 in your web browser.

Dependencies

• NVIDIA CUDA 12.4.0
• PyTorch 2.5.0
• JupyterLab
• iPyWidgets
• unsloth[cu124-torch250]

License

This project is licensed under the MIT License.

Contributing

Contributions are welcome! Please submit a pull request with your changes.