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Hugging Face Announces llama.cpp v1 as a Stable Release for Local AI

clem 🤗 · XRelayed· @ClementDelangue·· 16 hours agoPicks

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Original
Who
Hugging Face
What
announced the release of llama.cpp v1, its first major fully stable version

What happened

Hugging Face’s Clément Delangue announces llama.cpp v1 with Georgi Gerganov, describing it as the library’s first major fully stable version for running AI models locally on phones, laptops, and workstations. He says the release supports different hardware, platforms, and model types, and frames local use as a way to keep data private and retain control.

Why it matters

The post frames llama.cpp v1 as a stable release for running models locally and emphasizes community development and support across hardware, platforms, and model types.

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See the full storyHugging Face and Georgi Gerganov Announce llama.cpp v1
Article

We’re not going to win by lobbying, plotting, or manipulating. We’re going to win by building, in the open, with the whole community!

Today, with @ggerganov we’re super excited to announce the release of llama.cpp v1, the first major fully stable version of the most used library to run AI models locally, meaning on your phone, your laptop, and your workstation.

It means you can own your intelligence for free, not send your data to anyone and be 100% in control, wherever you are in the world. It shows our commitment to support every hardware, platform and model type out there and makes AI distributed rather than concentrated in a few Silicon Valley orgs.

Huge thanks to the team, the long-time maintainers and every contributor who helped make this happen. Let’s build! 💛🧡💚

Quoted postGeorgi Gerganov@ggerganov

llama.cpp v1.0.0 is now available

huggingface.co/blog/ggml-org/…

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The story so far

Hugging Face’s Clément Delangue and Georgi Gerganov announced llama.cpp v1 as the library’s first major fully stable version for running AI models locally on phones, laptops, and workstations. Delangue said it supports different hardware, platforms, and model types, and described local use as a way to keep data private and retain control.

This story is in 11/14 AI DailyRead the whole issue