Gpt Neo 2.7B 8bit

🚀 Quantized EleutherAI/gpt-neo-2.7B with 8-bit weights

This project provides a modified version of EleutherAI's GPT - Neo with 2.7 billion parameters, enabling model generation and fine - tuning on platforms like Colab or desktops with a single GPU (e.g., 1080Ti).

🚀 Quick Start

Here's how to run it:

✨ Features

This is a version of [EleutherAI's GPT - Neo](https://huggingface.co/EleutherAI/gpt - neo - 2.7B) with 2.7 billion parameters. It is modified so you can generate and fine - tune the model in colab or equivalent desktop gpu (e.g., single 1080Ti). It is inspired by [GPT - J 8bit](https://huggingface.co/hivemind/gpt - j - 6B - 8bit).

📚 Documentation

Model Description

GPT - Neo 2.7B is a transformer model designed using EleutherAI's replication of the GPT - 3 architecture. GPT - Neo refers to the class of models, while 2.7B represents the number of parameters of this particular pre - trained model.

🔗 Links

• EleutherAI
• [Hivemind](https://training - transformers - together.github.io/)
• Gustave Cortal

📄 License

This project is licensed under the MIT license.