Large language models (LLMs) serve as foundation models that generate text, translate between languages
Larger LLMs were always considered superior, but today companies realize they might be prohibitively expensive for research and innovation
Open source LLMs offer transparency and flexibility for companies without in-house machine learning talent, whether in the cloud or on premises
They cost less than proprietary LLMs over time since there are no licensing fees LLMs require cloud or on-premises infrastructure and a large initial installation cost
New features and community contributionsAdjustments are possible with open-source, pre-trained LLMs
What projects may open-source LLM models enable?
Falcon-40B, an Apache 2.0 LLM, can respond to a prompt with high-quality text suggestions you may tweak and improve