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Project Specification for Freelancer: Creating a GPT-NeoX Training Notebook on Shakespeare Dataset

Objective:

Develop an introductory Colab notebook that demonstrates a straightforward setup for training a small GPT-NeoX model on the Shakespeare dataset. This notebook will serve as an entry point for exploring GPT-NeoX model training, tailored for use on a T4 GPU in Google Colab. The goal is to create a lightweight, educational environment where team members can become familiar with the GPT-NeoX setup, configuration, and basic training workflow.

Key Requirements:

  1. Simple Model Setup:

    • Configure a small GPT-NeoX model that can be easily trained on a T4 GPU.
    • Keep the model parameters low to ensure training runs quickly and fits within Colab’s resource limits.

  2. Text Data Preparation (Shakespeare):

    • Utilize the Shakespeare text dataset to train the model.
    • Demonstrate basic data preparation techniques.

  3. Colab-Focused Setup:

    • Ensure the notebook is designed for easy execution in Google Colab with clear, beginner-friendly explanations.
    • Provide modular code sections to facilitate learning and exploration.

Notebook Structure and Content:

This notebook should guide the user step-by-step through setting up, configuring, and training a simple GPT-NeoX model on the Shakespeare dataset, with clear explanations of each section.

1. Introduction:

  • Objective Statement:

    • Briefly explain the notebook’s goal: setting up and training a small GPT-NeoX model on the Shakespeare dataset.

  • Overview of GPT-NeoX and its Capabilities:

    • Provide a short introduction to GPT-NeoX, with emphasis on why it’s a suitable model for language tasks.

2. GitHub and Collaboration Setup:

  • GitHub Repository Structure:

    • Organize the repository for collaborative development.

      /root
├── notebooks
│   └── shakespeare_training_notebook.ipynb
├── configs
│   └── shakespeare_config.yaml
├── data
│   └── (Data preparation instructions)
├── tokenizer
│   └── (Tokenizer files)
├── README.md
├── .gitignore
└── requirements.txt

  • GitHub Usage:

    • Set up a clear README.md with setup instructions.
    • Use GitHub issues or discussions for collaboration and feedback.

Expectations for the Freelancer:

  • Deliverables:

    • A Colab notebook (shakespeare_training_notebook.ipynb) that meets the above specifications.
    • A GitHub repository with configuration files, tokenizer, and data preparation scripts.
    • Clear instructions and comments in the notebook for users new to GPT-NeoX.

  • Code Quality:

    • Write clean, organized code with comments to explain each step.
    • Ensure reproducibility by documenting versions and setting random seeds.

  • Collaboration Setup:

    • Use GitHub for code sharing and version control.
    • Ensure W&B logging is implemented to enable experiment comparison.

  • Communication:

    • Regularly update on progress and request feedback if necessary.
    • Be open to revisions and adjustments based on team feedback.

Additional Considerations:

  • Data Privacy and Licensing:

    • Ensure the dataset and scripts comply with licensing and data privacy requirements.

  • Testing:

    • Test the notebook thoroughly to ensure it runs smoothly end-to-end on a T4 GPU.

  • User Experience:

    • Structure the notebook for a smooth learning experience, including error handling and debugging tips where needed.

Conclusion:

This notebook will serve as an accessible, entry-level guide to training GPT-NeoX on the Shakespeare dataset, focusing on simplicity and clarity. By leveraging GitHub for collaboration and W&B for experiment tracking, this project aims to provide an interactive

, exploratory environment for learning and experimenting with language model training.