I'm confused, is this from Meta? There's no attribution anywhere. Surely releasing an AI tool called llama breaks their trademark if not
llama.cpp
21–30 of 171 posts
Re: llama.cpp
#22Not sure why it's on the front page now, but I highly recommend using llama.cpp for running AI model locally vs using other inference framework, unless you have a very specific requirement. ggerganov and the team have done a stellar job maintaining the quality while still being fast to implement new models/improvements.
At this point the options are llama-server or vLLM if you're serious about running things at your desk in the under 256GB RAM size class (70B, 120B size models). In addition to, of course, 27B to 35B size things. With of course a ton of compile time build customization options for whatever specific hardware platform you want to run either llama or vllm on.
Re: llama.cpp
#23Anything that suggests curl into bash just plain sketches me out. (edit: I know, this isn't totally rational, it just seems weird to me. We download and trust a lot of software and run code from a bunch of package repositories as a regular activity...). Git clone llama.cpp and build it, it's not hard. https://github.com/ggml-org/llama.cpp/blob/master/docs/build... literally just a few steps for the basics: git clone…
You're not wrong about the appearance of sketchiness of that, but.... dude, come on. "It's not hard" is only true because you already know how to do it.
Re: llama.cpp
#24llama.cpp works pretty well for me on the Framework 13 laptop, but the current era of "move fast, break things, rarely fix" (sorry, that's how it feels), bites here quite a bit.
Two examples:
- https://github.com/ggml-org/llama.cpp/pull/25863 Someone's few lines change broke the native (ROCm) support for the AMD GPU inside Framework (and other integrated systems), and any rollback or proper fix is pending for almost a month. Fortunately there's workaround (switching to Vulkan rather than ROCm devices), but both the way the bug was introduced and the way it is not fixed just doesn't give much confidencen
- LM Studio is using llama.cpp internally for GGUF, they ship their own build with their closed source system as "runtimes". Their ROCm runtime does not enable the the AMD GPU inside the Framework, even thought the llama.cpp version would support it. So their runtime keeps telling me that there's no supported AMD GPU -- again, the solution is to use the GPU with the Vulkan devices. Not fixed since Jan at least https://github.com/lmstudio-ai/lmstudio-bug-tracker/issues/1...
I guess overall it's the worst runtime I've seen so far, except for all the other runtimes out there... I'm a fan, though in some cases I don't have enough knowledge, or I don't have access to fix things, and that feels like a bummer...
Re: llama.cpp
#25I'm confused, is this from Meta? There's no attribution anywhere. Surely releasing an AI tool called llama breaks their trademark if not
It's from https://github.com/ggml-org/llama.cpp -- not associated with Meta, it's been around for years, and surely they know about it -- so I would guess either it's not a trademark violation or they don't care.
Re: llama.cpp
#26Anything that suggests curl into bash just plain sketches me out. (edit: I know, this isn't totally rational, it just seems weird to me. We download and trust a lot of software and run code from a bunch of package repositories as a regular activity...). Git clone llama.cpp and build it, it's not hard. https://github.com/ggml-org/llama.cpp/blob/master/docs/build... literally just a few steps for the basics: git clone…
What would you win? Cmake is capable of executing shell commands and you end up with a binary that will execute on your machine anyway. At the end of the day it is just a matter of trust anyway, isn't it? I personally use bwrap if I'm not confident about the source.
Cloning a repo and building it is not _that_ hard, but easy installation is often the thing that makes or breaks a product. I believe Ollama proves that point in this context.
Re: llama.cpp
#27Anything that suggests curl into bash just plain sketches me out. (edit: I know, this isn't totally rational, it just seems weird to me. We download and trust a lot of software and run code from a bunch of package repositories as a regular activity...). Git clone llama.cpp and build it, it's not hard. https://github.com/ggml-org/llama.cpp/blob/master/docs/build... literally just a few steps for the basics: git clone…
You're not wrong about the appearance of sketchiness of that, but.... dude, come on. "It's not hard" is only true because you already know how to do it.
It's literally three steps, assuming you have the equivalent of the debian "build-essential" dependencies installed on your system for cmake, compiler. It's the exact three rows of my post, pasted one at a time into the CLI. The llama-server build guide page is actually pretty good.
I mean, sure, if there's people who can't figure that out, they're probably better off using a GUI that is a wrapper on top of somebody else's precompiled llama-server, like unsloth studio or lm studio. There's a good sized market for that and I wish them well.
Re: llama.cpp
#28Anything that suggests curl into bash just plain sketches me out. (edit: I know, this isn't totally rational, it just seems weird to me. We download and trust a lot of software and run code from a bunch of package repositories as a regular activity...). Git clone llama.cpp and build it, it's not hard. https://github.com/ggml-org/llama.cpp/blob/master/docs/build... literally just a few steps for the basics: git clone…
>Anything that suggests curl into bash just plain sketches me out. How is it different than trusting any other method of installation? If URL has https and is from an author you trust i dont see the difference.
Package management provides cryptographic attestation over the entire process, including the scripts run. Nothing is arbitrary nor mutable in the default state. The files touched will be in a predictable place and the scope of privilege escalation is clearly defined.
Re: llama.cpp
#29Is llama.cpp (and thus llama.app) really that much better than Ollama? I've Only ever played with Ollama, so geniously curious to hear other's real-world experiences.
Re: llama.cpp
#30Anything that suggests curl into bash just plain sketches me out. (edit: I know, this isn't totally rational, it just seems weird to me. We download and trust a lot of software and run code from a bunch of package repositories as a regular activity...). Git clone llama.cpp and build it, it's not hard. https://github.com/ggml-org/llama.cpp/blob/master/docs/build... literally just a few steps for the basics: git clone…
> Anything that suggests curl into bash just plain sketches me out. Yeah, 100% and it's becoming more and more of a thing, see rust install for example. OTOH, if you're installing llama.cpp, you're more than likely planning to run an LLM on your Linux box with an agentic harness, so a curl into bash thing might be the least of your security concerns, :-)
It's okay-ish for Rust because you only need the curl|bash for Rustup, which is meant as a development environment. On production you can, for example, use APT to download it from Debian.