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36 lines
1.2 KiB
ReStructuredText
36 lines
1.2 KiB
ReStructuredText
Export to ncnn
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==============
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We support exporting the following models
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to `ncnn <https://github.com/tencent/ncnn>`_:
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- `Zipformer transducer models <https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/pruned_transducer_stateless7_streaming>`_
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- `LSTM transducer models <https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/lstm_transducer_stateless2>`_
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- `ConvEmformer transducer models <https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/conv_emformer_transducer_stateless2>`_
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We also provide `sherpa-ncnn`_
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for performing speech recognition using `ncnn`_ with exported models.
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It has been tested on the following platforms:
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- Linux
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- macOS
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- Windows
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- ``Android``
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- ``iOS``
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- ``Raspberry Pi``
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- `爱芯派 <https://wiki.sipeed.com/hardware/zh/>`_ (`MAIX-III AXera-Pi <https://wiki.sipeed.com/hardware/en/maixIII/ax-pi/axpi.html>`_).
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`sherpa-ncnn`_ is self-contained and can be statically linked to produce
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a binary containing everything needed. Please refer
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to its documentation for details:
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- `<https://k2-fsa.github.io/sherpa/ncnn/index.html>`_
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.. toctree::
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export-ncnn-conv-emformer
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export-ncnn-lstm
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