Showing 5 open source projects for "linux device driver project"

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  • 1
    stable-diffusion.cpp

    stable-diffusion.cpp

    Diffusion model (SD, Flux, Wan, Qwen Image, Z-Image...) inference

    stable-diffusion.cpp is a lightweight, high-performance implementation of Stable Diffusion and related generative models written entirely in portable C/C++, designed to run on virtually any device without heavy dependencies. It enables text-to-image and image-to-image generation, supports a growing set of models like SD1.x, SD2.x, SDXL, SD-Turbo, Qwen Image, and more, and is continually updated with support for cutting-edge model variants including video and image editing models. The project...
    Downloads: 101 This Week
    Last Update:
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  • 2
    MobileCLIP

    MobileCLIP

    Implementation of "MobileCLIP" CVPR 2024

    MobileCLIP is a family of efficient image-text embedding models designed for real-time, on-device retrieval and zero-shot classification. The repo provides training, inference, and evaluation code for MobileCLIP models trained on DataCompDR, and for newer MobileCLIP2 models trained on DFNDR. It includes an iOS demo app and Core ML artifacts to showcase practical, offline photo search and classification on iPhone-class hardware. Project notes highlight latency/accuracy trade-offs, with...
    Downloads: 0 This Week
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  • 3
    ESP32 iPhone Agent

    ESP32 iPhone Agent

    Let an AI model use a real iPhone with a $7 ESP32

    ESP32 iPhone Agent is an open-source hardware and software project that enables AI models to interact with a physical iPhone using an inexpensive ESP32-S3 microcontroller. It combines AirPlay screen mirroring with USB Human Interface Device emulation to provide an AI agent with visual feedback and physical input capabilities. The ESP32-S3 receives the phone's screen stream and relays visual information to an iPhone application for AI analysis. Compatible vision models interpret screenshots...
    Downloads: 3 This Week
    Last Update:
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  • 4
    Cactus Needle

    Cactus Needle

    26m function call model that runs on incredibly small devices

    Needle is an experimental 26-million-parameter function-calling model designed to run on extremely small devices such as phones, watches, glasses, and low-power personal AI hardware. It is based on a Simple Attention Network architecture and was distilled from a much larger model to focus on fast, compact tool-use behavior. The project provides open weights, training details, dataset generation resources, and a playground for testing the model with custom tools. Needle is optimized for...
    Downloads: 0 This Week
    Last Update:
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  • 5
    HY-MT

    HY-MT

    Hunyuan Translation Model Version 1.5

    HY-MT (Hunyuan Translation) is a high-quality multilingual machine translation model suite developed to support mutual translation across dozens of languages with strong performance even at smaller model scales. It ships with both an 1.8 B parameter model and a larger 7 B model, the latter optimized not only for direct translation but also for formatted and contextualized output, allowing better handling of terminology and mixed-language content. The project emphasizes both speed and...
    Downloads: 2 This Week
    Last Update:
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