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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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pipeline_tag: text-to-speech |
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tags: |
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- text-generation-inference |
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--- |
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# GLaDOS |
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## Training |
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This was trained with the ipython notebok [HERE](https://github.com/davesarmoury/GLaDOS/blob/main/TrainNemo/Train_NeMo.ipynb) |
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## RIVA |
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Look here [https://docs.nvidia.com/deeplearning/riva/user-guide/docs/quick-start-guide.html](https://docs.nvidia.com/deeplearning/riva/user-guide/docs/quick-start-guide.html) |
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### On Local Machine |
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pip3 install whl |
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pip3 install nemo2riva |
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nemo2riva --out hifigan.riva hifigan.nemo --key None |
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nemo2riva --out fastpitch.riva fastpitch.nemo --key None |
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scp .riva files to jetson under ~/RIVA/artifacts |
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### On Jetson |
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docker run --gpus all -it --rm \ |
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-v /home/davesarmoury/RIVA/artifacts:/servicemaker-dev \ |
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-v /home/davesarmoury/RIVA/riva_repo:/data \ |
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--entrypoint="/bin/bash" \ |
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nvcr.io/nvidia/riva/riva-speech:2.13.1-servicemaker-l4t-aarch64 |
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riva-build speech_synthesis \ |
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/servicemaker-dev/glados.rmir:tlt_encode \ |
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/servicemaker-dev/glados_fastpitch.riva:tlt_encode \ |
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/servicemaker-dev/glados_hifigan.riva:tlt_encode \ |
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--voice_name=GLaDOS \ |
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--sample_rate 22050 |
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riva-deploy /servicemaker-dev/glados.rmir:tlt_encode /data/models |
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# Exit docker |
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ngc registry resource download-version nvidia/riva/riva_quickstart_arm64:2.13.1 |
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cd riva_quickstart_arm64_v2.13.1 |
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bash riva_init.sh |
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copy glados.riva files into riva models dir |
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riva_start.sh |
