Showing 3 open source projects for "lora"

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  • 1
    stable-diffusion.cpp

    stable-diffusion.cpp

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

    ...The project is built on the ggml backend, which allows efficient execution on CPUs and GPUs via backends like CUDA, Vulkan, Metal, OpenCL, and SYCL, making it suitable for everything from desktops to mobile devices. It includes options for ControlNet, LoRA models, upscaling via ESRGAN, and advanced sampling techniques, giving developers and users a rich toolkit for creative workflows.
    Downloads: 36 This Week
    Last Update:
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  • 2
    qvac-fabric-llm.cpp

    qvac-fabric-llm.cpp

    QVAC Fabric: cross-platform LLM inference and fine-tuning

    ...The project focuses on removing hardware limitations traditionally associated with LLM deployment by enabling support for a wide range of backends, including Vulkan, Metal, CUDA, and CPU, making it accessible on devices ranging from smartphones to enterprise servers. It introduces native LoRA fine-tuning capabilities that can be executed directly on consumer hardware, allowing developers to train and adapt models locally without relying on cloud infrastructure. A key innovation is its support for BitNet ternary quantized models, enabling highly efficient inference and training even on resource-constrained systems.
    Downloads: 3 This Week
    Last Update:
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  • 3
    Alpaca.cpp

    Alpaca.cpp

    Locally run an Instruction-Tuned Chat-Style LLM

    ...This combines the LLaMA foundation model with an open reproduction of Stanford Alpaca a fine-tuning of the base model to obey instructions (akin to the RLHF used to train ChatGPT) and a set of modifications to llama.cpp to add a chat interface. Download the zip file corresponding to your operating system from the latest release. The weights are based on the published fine-tunes from alpaca-lora, converted back into a PyTorch checkpoint with a modified script and then quantized with llama.cpp the regular way.
    Downloads: 4 This Week
    Last Update:
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