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  • 1
    SenseVoice

    SenseVoice

    Multilingual speech recognition and audio understanding model

    ...It is built to achieve high transcription accuracy while maintaining efficient inference performance. It includes different model variants optimized for either speed or accuracy, allowing developers to choose a configuration suitable for their use case. In addition to speech transcription, SenseVoice can detect emotional cues in speech and identify common sound events such as applause, laughter, or coughing. It also provides tools for running inference, exporting models to formats like ONNX or LibTorch, and deploying the system through APIs.
    Downloads: 8 This Week
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  • 2
    Caffe2

    Caffe2

    Caffe2 is a lightweight, modular, and scalable deep learning framework

    ...Modularity and being designed for both scale and mobile deployments are the high-level answers to the first question. In many ways Caffe2 is an un-framework because it is so flexible and modular. The original Caffe framework was useful for large-scale product use cases, especially with its unparalleled performance and well tested C++ codebase. Caffe has some design choices that are inherited from its original use case: conventional CNN applications.
    Downloads: 0 This Week
    Last Update:
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