678: StableLM: Open-source "ChatGPT"-like LLMs you can fit on one GPU — with @JonKrohnLearns

Pre-training

The pre-training data for StableLM models is a game-changer in the realm of language models. Jon Krohn highlights that StableLM's dataset is three times larger than previous datasets, boasting 1.5 trillion tokens 1. This vast dataset allows the model to have 267 times more tokens than parameters, which is unprecedented for a model of its size.

This should lead to an amazing model.

--- Jon Krohn

Such a large dataset is expected to significantly enhance the model's performance, potentially surpassing previous benchmarks 1.

   

Fine-Tuning

Fine-tuning is crucial for achieving GPT-4 like results with StableLM. Jon explains that the model uses the Alpaca procedure, incorporating over a million instruction-response pairs from various sources, including GPT-4 and Dall-E 2. This extensive fine-tuning dataset is 100 times larger than that used for Dall-E 2.0, enhancing the model's capabilities.

You can even go right now to chat interactively with the fine-tuned 7 billion parameter stable LM model.

--- Jon Krohn

The open-source nature of StableLM allows users to experiment with and fine-tune the models for their own purposes, promising exciting developments in AI 2.