We are super happy to announce that GGML, creators of Llama.cpp, are joining HF in order to keep future AI open. 🔥 Georgi Gerganov and team are joining HF with the goal of scaling and supporting the community behind ggml and llama.cpp as Local AI continues to make exponential progress in the coming years.

We've been working with Georgi and team for quite some time (we even have awesome core contributors to llama.cpp like Son and Alek in the team already) so this has been a very natural process.

llama.cpp is the fundamental building block for local inference, and transformers is the fundamental building block for model definition, so this is basically a match made in heaven. ❤️

What will change for llama.cpp, the open source project and the community?

Not much – Georgi and team still dedicate 100% of their time maintaining llama.cpp and have full autonomy and leadership on the technical directions and the community. HF is providing the project with long-term sustainable resources, improving the chances of the project to grow and thrive. The project will continue to be 100% open-source and community driven as it is now.

Technical focus

llama.cpp is the fundamental building block for local inference, and transformers is the fundamental building block for definition of models and architectures, so we’ll work on making sure it’s as seamless as possible in the future (almost “single-click”) to ship new models in llama.cpp from the transformers library ‘source of truth’ for model definitions.

Additionally, we will improve packaging and user experience of ggml-based software. As we enter the phase in which local inference becomes a meaningful and competitive alternative to cloud inference, it is crucial to improve and simplify the way in which casual users deploy and access local models. We will work towards making llama.cpp ubiquitous and readily available everywhere.

Our long term vision

Our shared goal is to provide the community with the building blocks to make open-source superintelligence accessible to the world over the coming years.

We will achieve this together with the growing Local AI community, as we continue to build the ultimate inference stack that runs as efficiently as possible on our devices.