Showing 12 open source projects for "32 bit linux"

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  • 1
    AIMET

    AIMET

    AIMET is a library that provides advanced quantization and compression

    ...Quantized inference is significantly faster than floating point inference. For example, models that we’ve run on the Qualcomm® Hexagon™ DSP rather than on the Qualcomm® Kryo™ CPU have resulted in a 5x to 15x speedup. Plus, an 8-bit model also has a 4x smaller memory footprint relative to a 32-bit model. However, often when quantizing a machine learning model (e.g., from 32-bit floating point to an 8-bit fixed point value), the model accuracy is sacrificed.
    Downloads: 0 This Week
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  • 2
    CTranslate2

    CTranslate2

    Fast inference engine for Transformer models

    CTranslate2 is a C++ and Python library for efficient inference with Transformer models. The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many...
    Downloads: 27 This Week
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  • 3
    LitGPT

    LitGPT

    20+ high-performance LLMs with recipes to pretrain, finetune at scale

    LitGPT is a collection of over 20 high-performance large language models (LLMs) accompanied by recipes to pretrain, finetune, and deploy them at scale. It provides implementations without abstractions, making it beginner-friendly while offering advanced features like flash attention and support for various precision levels. LitGPT is designed to run efficiently across multiple GPUs or TPUs, catering to both small-scale and large-scale deployments.
    Downloads: 0 This Week
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  • 4
    Transformer Engine

    Transformer Engine

    A library for accelerating Transformer models on NVIDIA GPUs

    Transformer Engine (TE) is a library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference. TE provides a collection of highly optimized building blocks for popular Transformer architectures and an automatic mixed precision-like API that can be used seamlessly with your framework-specific code. TE also includes a framework-agnostic C++...
    Downloads: 1 This Week
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  • 5
    ollama_manager_gui

    ollama_manager_gui

    A graphical manager for ollama that can manage your LLMs

    This app will help install ollama and LLMs using the gui provided by this app. It checks for ollama when launched and if it doesn't exist it will help by bringing you to the ollama site for download. This app is heavily upgraded and now also works properly on Linux. It now has progress bars and many many many improvements. It can launch the LLM by clicking the link. it can launch multiple LLMs in separate windows. It can also remove an installed LLM. There is a confirmation...
    Downloads: 4 This Week
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  • 6
    Neural Speed

    Neural Speed

    An innovative library for efficient LLM inference

    neural-speed is an innovative library developed by Intel to enhance the efficiency of Large Language Model (LLM) inference through low-bit quantization techniques. By reducing the precision of model weights and activations, neural-speed aims to accelerate inference while maintaining model accuracy, making it suitable for deployment in resource-constrained environments.
    Downloads: 0 This Week
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  • 7
    Curated Transformers

    Curated Transformers

    PyTorch library of curated Transformer models and their components

    State-of-the-art transformers, brick by brick. Curated Transformers is a transformer library for PyTorch. It provides state-of-the-art models that are composed of a set of reusable components. Supports state-of-the-art transformer models, including LLMs such as Falcon, Llama, and Dolly v2. Implementing a feature or bugfix benefits all models. For example, all models support 4/8-bit inference through the bitsandbytes library and each model can use the PyTorch meta device to avoid unnecessary...
    Downloads: 0 This Week
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  • 8
    AutoGPTQ

    AutoGPTQ

    An easy-to-use LLMs quantization package with user-friendly apis

    AutoGPTQ is an implementation of GPTQ (Quantized GPT) that optimizes large language models (LLMs) for faster inference by reducing their computational footprint while maintaining accuracy.
    Downloads: 0 This Week
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  • 9
    FastChat

    FastChat

    Open platform for training, serving, and evaluating language models

    ...This requires 8-bit compression to be enabled and the bitsandbytes package to be installed, which is only available on linux operating systems.
    Downloads: 0 This Week
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  • 10
    LLaVA

    LLaVA

    Visual Instruction Tuning: Large Language-and-Vision Assistant

    Visual instruction tuning towards large language and vision models with GPT-4 level capabilities.
    Downloads: 3 This Week
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  • 11
    llama2-webui

    llama2-webui

    Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere

    Running Llama 2 with gradio web UI on GPU or CPU from anywhere (Linux/Windows/Mac).
    Downloads: 0 This Week
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  • 12
    spaGO

    spaGO

    Self-contained Machine Learning and Natural Language Processing lib

    A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. In other words, it has "zero dependencies", and we are committed to keeping it that way as much as possible. Spago uses a multi-module workspace to...
    Downloads: 0 This Week
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