Showing 5 open source projects for "support vector machine"

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  • 1
    Lingvo

    Lingvo

    Framework for building neural networks

    ...Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably.
    Downloads: 0 This Week
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  • 2
    MeloTTS

    MeloTTS

    High-quality multi-lingual text-to-speech library by MyShell.ai

    MeloTTS is an open-source text-to-speech (TTS) system that generates natural-sounding speech from text input. It utilizes advanced machine-learning models to produce high-quality audio outputs.
    Downloads: 9 This Week
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  • 3
    AudioBC

    AudioBC

    Offline desktop app to convert EPUB to MP3 using Kokoro-82M neural TTS

    ...Privacy-First & Offline: After a one-time initial model download, all processing happens on your CPU. Your books never leave your computer. Multi-Language Support: Curated voices for English (US & UK), Italian, French, Spanish, and Portuguese (BR). Smart Extraction: Automatically filters out non-narrative cont
    Downloads: 0 This Week
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  • 4
    PaddlePaddle models

    PaddlePaddle models

    Pre-trained and Reproduced Deep Learning Models

    Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,...
    Downloads: 1 This Week
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    OpenSeq2Seq

    OpenSeq2Seq

    Toolkit for efficient experimentation with Speech Recognition

    ...Its core goal is to give researchers a flexible, modular framework for building and training encoder–decoder architectures while fully leveraging distributed and mixed-precision training. The toolkit includes ready-made models for neural machine translation, automatic speech recognition, speech synthesis, language modeling, and additional NLP tasks such as sentiment analysis. It supports multi-GPU and multi-node data-parallel training, and integrates with Horovod to scale out across large GPU clusters. Mixed-precision support (float16) is optimized for NVIDIA Volta and Turing GPUs, allowing significant speedups and memory savings without sacrificing model quality. ...
    Downloads: 0 This Week
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