Showing 4 open source projects for "python package"

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  • 1
    BioEmu

    BioEmu

    Inference code for scalable emulation of protein equilibrium ensembles

    Biomolecular Emulator (BioEmu for short) is a model that samples from the approximated equilibrium distribution of structures for a protein monomer, given its amino acid sequence. By default, unphysical structures (steric clashes or chain discontinuities) will be filtered out, so you will typically get fewer samples in the output than requested. The difference can be very large if your protein has large disordered regions, which are very likely to produce clashes. BioEmu outputs structures...
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  • 2
    mms-300m-1130-forced-aligner

    mms-300m-1130-forced-aligner

    CTC-based forced aligner for audio-text in 158 languages

    ... to the TorchAudio forced alignment API. Users can integrate it easily through the Python package ctc-forced-aligner, and it supports GPU acceleration via PyTorch. The alignment pipeline includes audio processing, emission generation, tokenization, and span detection, making it suitable for speech analysis, transcription syncing, and dataset creation. This model is especially useful for researchers and developers working with low-resource languages or building multilingual speech systems.
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  • 3
    Dia-1.6B

    Dia-1.6B

    Dia-1.6B generates lifelike English dialogue and vocal expressions

    ... on enterprise GPUs, though CPU and quantized versions are planned. The format supports [S1]/[S2] tags to differentiate speakers and integrates easily into Python workflows. While not tuned to a specific voice, user-provided audio can guide output style. Licensed under Apache 2.0, Dia is intended for research and educational use, with explicit restrictions on misuse like identity mimicry or deceptive content.
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  • 4
    chronos-t5-small

    chronos-t5-small

    Time series forecasting model using T5 architecture with 46M params

    ... probabilistic forecasting by autoregressively sampling multiple future trajectories. The model is capable of generating full predictive distributions, making it well-suited for uncertainty-aware forecasting. It is compatible with the Chronos Python package and integrates easily into forecasting pipelines using PyTorch. Chronos models are open-source under Apache 2.0 and have been demonstrated to perform competitively in forecasting benchmarks.
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