Showing 8 open source projects for "cuda"

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  • 1
    stable-diffusion.cpp

    stable-diffusion.cpp

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

    ...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 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: 40 This Week
    Last Update:
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  • 2
    DeepGEMM

    DeepGEMM

    Clean and efficient FP8 GEMM kernels with fine-grained scaling

    DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries.
    Downloads: 1 This Week
    Last Update:
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  • 3
    DeepSeek-V3.2-Exp

    DeepSeek-V3.2-Exp

    An experimental version of DeepSeek model

    ...MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. The repository includes tools and kernels to support the new sparse architecture—for instance, CUDA kernels, logit indexers, and open-source modules like FlashMLA and DeepGEMM are invoked for performance.
    Downloads: 8 This Week
    Last Update:
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  • 4
    xFormers

    xFormers

    Hackable and optimized Transformers building blocks

    ...One of its key goals is efficient attention: it supports dense, sparse, low-rank, and approximate attention mechanisms (e.g. FlashAttention, Linformer, Performer) via interchangeable modules. The library includes memory-efficient operator implementations in both Python and optimized C++/CUDA, ensuring that performance isn’t sacrificed for modularity. It also integrates with PyTorch seamlessly so you can drop in its blocks to existing models, replace default attention layers, or build new architectures from scratch. xformers includes training, deployment, and memory profiling tools.
    Downloads: 1 This Week
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  • 5
    4M

    4M

    4M: Massively Multimodal Masked Modeling

    ...The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things like depth tokenizers, input masks for generation, and CUDA build questions, signaling active research iteration. The design leans into flexibility and steerability, so prompts and masks can shape behavior without bespoke heads per task. In short, 4M provides a unified recipe to pretrain large multimodal models that generalize broadly while remaining practical to fine-tune.
    Downloads: 0 This Week
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  • 6
    Miso TTS

    Miso TTS

    Miso TTS is an 8 billion, highly emotive text-to-speech model

    Miso TTS is an advanced 8-billion-parameter text-to-speech model developed by Miso Labs for generating highly expressive and natural-sounding conversational speech. Built on an RVQ Transformer architecture inspired by Sesame CSM, it combines a powerful Llama-based backbone with an autoregressive audio decoder to produce high-quality audio from text. The model supports both standard speech synthesis and voice-conditioned generation using optional audio prompts for voice cloning. Miso TTS...
    Downloads: 1 This Week
    Last Update:
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  • 7
    Warlock-Studio

    Warlock-Studio

    AI Suite for upscaling, interpolating & restoring images/videos

    v6.0. Warlock-Studio is a Windows application that uses Real-ESRGAN, BSRGAN, IRCNN, GFPGAN, RealESRNet, RealESRAnime and RIFE Artificial Intelligence models to upscale, restore faces, interpolate frames and reduce noise in images and videos. the application supports GPU acceleration (including multi-GPU setups) and offers batch processing for large workloads. It includes drag-and-drop handling for single or multiple files, optional pre-resize functions, and an automatic tiling system...
    Downloads: 35 This Week
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  • 8
    CSM (Conversational Speech Model)

    CSM (Conversational Speech Model)

    A Conversational Speech Generation Model

    ...The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution.
    Downloads: 3 This Week
    Last Update:
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