Showing 7 open source projects for "macos linux os"

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  • Build Agents and Models on One Platform Icon
    Build Agents and Models on One Platform

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    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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  • 1
    GPT4All

    GPT4All

    Run Local LLMs on Any Device. Open-source

    GPT4All is an open-source project that allows users to run large language models (LLMs) locally on their desktops or laptops, eliminating the need for API calls or GPUs. The software provides a simple, user-friendly application that can be downloaded and run on various platforms, including Windows, macOS, and Ubuntu, without requiring specialized hardware. It integrates with the llama.cpp implementation and supports multiple LLMs, allowing users to interact with AI models privately. This...
    Downloads: 110 This Week
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  • 2
    Distributed Llama

    Distributed Llama

    Connect home devices into a powerful cluster to accelerate LLM

    ...By leveraging tensor parallelism and high-speed synchronization over Ethernet, it allows for faster performance as more devices are added to the cluster. The system supports various operating systems, including Linux, macOS, and Windows, and is optimized for both ARM and x86_64 AVX2 CPUs.
    Downloads: 1 This Week
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  • 3
    LLM.swift

    LLM.swift

    LLM.swift is a simple and readable library

    LLM.swift is a Swift package that enables developers to run Large Language Models (LLMs) directly on Apple devices, including iOS, macOS, and watchOS. By leveraging Apple's hardware and software optimizations, LLM.swift facilitates on-device natural language processing tasks, ensuring user privacy and reducing latency associated with cloud-based solutions.​
    Downloads: 0 This Week
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  • 4
    Gitleaks

    Gitleaks

    Protect and discover secrets using Gitleaks

    Gitleaks is a fast, lightweight, portable, and open-source secret scanner for git repositories, files, and directories. With over 6.8 million docker downloads, 11.2k GitHub stars, 1.7 million GitHub Downloads, thousands of weekly clones, and over 400k homebrew installs, gitleaks is the most trusted secret scanner among security professionals, enterprises, and developers. Gitleaks-Action is our official GitHub Action. You can use it to automatically run a gitleaks scan on all your team's pull...
    Downloads: 25 This Week
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  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

    Learn how to protect your Microsoft 365 data, with simple, actionable tips today.

    Watch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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  • 5
    rwkv.cpp

    rwkv.cpp

    INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model

    Besides the usual FP32, it supports FP16, quantized INT4, INT5 and INT8 inference. This project is focused on CPU, but cuBLAS is also supported. RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths.
    Downloads: 0 This Week
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  • 6
    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI swift async text to image for SwiftUI app using OpenAI

    SwiftUI views that asynchronously loads and displays an OpenAI image from open API. You just type in your idea and AI will give you an art solution. DALL-E and DALL-E 2 are deep learning models developed by OpenAI to generate digital images from natural language descriptions, called "prompts". You need to have Xcode 13 installed in order to have access to Documentation Compiler (DocC) OpenAI's text-to-image model DALL-E 2 is a recent example of diffusion models. It uses diffusion models for...
    Downloads: 0 This Week
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  • 7
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    ...In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference.
    Downloads: 62 This Week
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