Audio-to-Audio
MambaSSM
Safetensors
streaming speech-enhancement
speech-enhancement
universal speech enhancement
multiple input sampling rates
language-agnostic
Instructions to use nvidia/Real-time_RE-USE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MambaSSM
How to use nvidia/Real-time_RE-USE with MambaSSM:
from mamba_ssm import MambaLMHeadModel model = MambaLMHeadModel.from_pretrained("nvidia/Real-time_RE-USE") - Notebooks
- Google Colab
- Kaggle
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README.md
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Directly try our [**Gradio Interactive Demo**](https://huggingface.co/spaces/nvidia/Real-time_RE-USE) by uploading your noisy audio/video !!
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!! Note that this demo page uses offline inference, so you can easily check the audio quality not the latency.
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## Environment Setup
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1. (For **Mamba** setup)Pre-built Docker environments can be downloaded [here](https://github.com/RoyChao19477/SEMamba?tab=readme-ov-file#-docker-support) to simplify **Mamba** setup.
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Directly try our [**Gradio Interactive Demo**](https://huggingface.co/spaces/nvidia/Real-time_RE-USE) by uploading your noisy audio/video !!
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!! Note that this demo page uses offline inference, so you can easily check the audio quality not the latency.
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Please refer to `online_inference.py` and `online_inference.sh` for streaming inference.
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## Environment Setup
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1. (For **Mamba** setup)Pre-built Docker environments can be downloaded [here](https://github.com/RoyChao19477/SEMamba?tab=readme-ov-file#-docker-support) to simplify **Mamba** setup.
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