Showing 2 open source projects for "ram linux"

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    OnnxStream

    OnnxStream

    Lightweight inference library for ONNX files, written in C++

    The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which...
    Downloads: 11 This Week
    Last Update:
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  • 2
    LLaMA.go

    LLaMA.go

    llama.go is like llama.cpp in pure Golang

    llama.go is like llama.cpp in pure Golang. The code of the project is based on the legendary ggml.cpp framework of Georgi Gerganov written in C++ with the same attitude to performance and elegance. Both models store FP32 weights, so you'll needs at least 32Gb of RAM (not VRAM or GPU RAM) for LLaMA-7B. Double to 64Gb for LLaMA-13B.
    Downloads: 0 This Week
    Last Update:
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