metal-cpp
llama.cpp
metal-cpp | llama.cpp | |
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16 | 776 | |
250 | 57,463 | |
- | - | |
3.3 | 10.0 | |
4 months ago | 6 days ago | |
C++ | C++ | |
Apache License 2.0 | MIT License |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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metal-cpp
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Nitro: A fast, lightweight 3MB inference server with OpenAI-Compatible API
My understanding is the proliferation of “XYZ-cpp” AI frameworks is due to the c++ support in Apple’s gpu library ‘Metal’, and the popularity of apple silicon for inference (and there are a few technical reasons for this): https://developer.apple.com/metal/cpp/
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Show HN: C-ocoa, Write iOS/macOS apps in any language, with a generated C API
This is basically also what the "official" C++ API for Metal does (https://developer.apple.com/metal/cpp/), it's an automatically generated bindings wrapper which calls into ObjC runtime functions.
I also dabbled a bit with this idea by parsing clang AST-dumps of macOS system headers:
https://github.com/floooh/objc-ast-experiments
Unfortunately this is very brittle, and also broke on ARM CPUs, I guess the shim code needs some ABI adjustments (famously, objc_msgSend has multiple "ABI shapes": https://www.mikeash.com/pyblog/objc_msgsends-new-prototype.h...).
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What's the best way to learn Metal?
There's official C++-interface: https://developer.apple.com/metal/cpp/
- What are some alternatives to OpenGL for Mac
- Opinion for graphic api's?
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A brief interview with Tcl creator John Ousterhout
It doesn't matter if the project driven by Microsoft or not, the cat (of automatically generated language bindings) is out of the bag. E.g. Zig is using the same approach without being an official MS project: https://github.com/marlersoft/zigwin32, and Apple has an automatically generated C++ API for Metal (https://developer.apple.com/metal/cpp/).
In the future, the question won't be "what language do I need to learn to code on this platform", but instead "are there language bindings for my favourite language".
- Cross platform low level graphics API suitable for game development?
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GCC now includes Modula-2 and Rust. Do they work on OpenBSD?
this? https://developer.apple.com/metal/cpp/
Doesn't it just use objc/runtime.h and if anything is missing you can just add your custom api calls?
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A learning path for Vulkan that focuses on concepts?
Metal has C++ bindings (which cover a full app lifecycle so you don’t have to touch Objective-C/Swift at all) but they’re based on the Objective-C memory model. There are some helper structs mimicking shared pointers, but you’ll still need to understand the basics of how an autorelease pool is used to avoid memory leaks and/or bad access crashes.
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CTO of Azure declares C++ "deprecated"
On https://developer.apple.com/metal/cpp/ check Foundation folder and all those nice Object::sendMessage().
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
MoltenVK - MoltenVK is a Vulkan Portability implementation. It layers a subset of the high-performance, industry-standard Vulkan graphics and compute API over Apple's Metal graphics framework, enabling Vulkan applications to run on macOS, iOS and tvOS.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
Cinder - Cinder is a community-developed, free and open source library for professional-quality creative coding in C++.
gpt4all - gpt4all: run open-source LLMs anywhere
LearnOpenGL - Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
objc4
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
metal-rs - Rust bindings for Metal
ggml - Tensor library for machine learning
OpenFrameworks - openFrameworks is a community-developed cross platform toolkit for creative coding in C++.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM