---
language: en
tags:
- pytorch
- gpt2
- text-generation
license: mit
datasets:
- Skylion007/openwebtext
model-index:
- name: chatMachineProto
  results: []
---

# NanoGPT Personal Experiment

This repository contains my personal experiment with training and fine-tuning a GPT-2 style language model. This project was undertaken as a learning exercise to understand transformer-based language models and explore the capabilities of modern AI architectures.

## Model Description

This model is based on the nanoGPT implementation, which is a minimal, clean implementation of GPT-2 style models. The architecture follows the original GPT-2 design principles while being more accessible and easier to understand.

### Technical Details

- Base Architecture: GPT-2
- Training Infrastructure: 8x A100 80GB GPUs
- Parameters: ~124M (similar to GPT-2 small)

### Training Process

The model underwent a multi-stage training process:
- Initial training on a subset of the OpenWebText dataset
- Experimentation with different hyperparameters and optimization techniques

### Features

- Clean, minimal implementation of the GPT architecture
- Efficient training utilizing modern GPU capabilities
- Configurable generation parameters (temperature, top-k sampling)
- Support for both direct text generation and interactive chat

## Use Cases

This model is primarily an experimental project and can be used for:
- Educational purposes to understand transformer architectures
- Text generation experiments
- Research into language model behavior
- Interactive chat experiments

## Limitations

As this is a personal experiment, please note:
- The model may produce inconsistent or incorrect outputs
- It's not intended for production use
- Responses may be unpredictable or contain biases
- Performance may vary significantly depending on the input

## Development Context

This project was developed as part of my personal exploration into AI/ML, specifically focusing on:
- Understanding transformer architectures
- Learning about large-scale model training
- Experimenting with different training approaches
- Gaining hands-on experience with modern AI infrastructure

## Acknowledgments

This project builds upon the excellent work of:
- The original GPT-2 paper by OpenAI
- The nanoGPT implementation by Andrej Karpathy
- The broader open-source AI community

## Disclaimer

This is a personal experimental project and should be treated as such. It's not intended for production use or as a replacement for more established language models. The primary goal was learning and experimentation.

---

Feel free to explore the model and provide feedback. Remember that this is an experimental project, and results may vary significantly from more established models.