Showing 3 open source projects for "multi"

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    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

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    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

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    Supertonic

    Supertonic

    Lightning-fast, on-device TTS, running natively via ONNX

    Supertonic is a lightning-fast, on-device text-to-speech system built around ONNX Runtime for maximum speed and portability. It focuses on running entirely locally, eliminating the need for cloud APIs and providing low latency and strong privacy guarantees, even on constrained devices like Raspberry Pi boards and e-readers. The core model is highly compact at around 66 million parameters, yet benchmarks show it can generate speech up to 167× faster than real time on modern consumer hardware...
    Downloads: 2 This Week
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  • 2
    comfyui-mixlab-nodes

    comfyui-mixlab-nodes

    Workflow and speech recognition app

    comfyui-mixlab-nodes is a large collection of custom nodes for ComfyUI that turns workflows into interactive apps and adds real-time multimedia, LLM, and TTS capabilities. It introduces a “Workflow-to-APP” concept, where a ComfyUI graph can be transformed into a Web App through an AppInfo node, complete with categories, batch prompts, and editable configurations. The project also brings Real-time Design features like screen capture and floating video nodes, enabling creative pipelines that...
    Downloads: 3 This Week
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  • 3
    XZVoice

    XZVoice

    Free and open source text-to-speech software

    ...The high-fidelity and flexible configuration of speech synthesis products opens up the closed loop of human-computer interaction and enables applications to sound realistically. A variety of timbres are available, and functions such as adjusting speech rate, intonation, and volume are provided. Technically, multi-level rhythmic pauses are taken into account to achieve the purpose of natural synthesizing rhythm, and comprehensively use acoustic parameters and linguistic parameters to establish multiple automatic prediction models based on deep learning. Using massive audio data to train the pronunciation model, the synthetic sound is real, full, cadenced, and expressive, and the MOS score has reached the professional level in the industry.
    Downloads: 0 This Week
    Last Update:
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