Audio-to-Audio
MambaSSM
Safetensors
speech-enhancement
universal speech enhancement
multiple input sampling rates
language-agnostic
Instructions to use nvidia/RE-USE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MambaSSM
How to use nvidia/RE-USE with MambaSSM:
from mamba_ssm import MambaLMHeadModel model = MambaLMHeadModel.from_pretrained("nvidia/RE-USE") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Usage
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Directly try our [**Gradio Interactive Demo**](https://huggingface.co/spaces/nvidia/RE-USE) by uploading your noisy audio/video !!
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## Environment
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Pre-built Docker environments can be downloaded [here](https://github.com/RoyChao19477/SEMamba?tab=readme-ov-file#-docker-support) to simplify setup.
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If you need bandwidth extension:
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```bash
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pip install resampy
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```
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## Inference
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Follow the simple steps below to generate enhanced speech using our model:
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1. Place your noisy speech files in the folder `noisy_audio/`
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## Usage
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Directly try our [**Gradio Interactive Demo**](https://huggingface.co/spaces/nvidia/RE-USE) by uploading your noisy audio/video !!
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## Environment Setup
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1. 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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2. If you need bandwidth extension:
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```bash
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pip install resampy
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```
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3. Download and navigate to the HuggingFace repository:
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```
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huggingface-cli download nvidia/RE-USE --local-dir ./REUSE --local-dir-use-symlinks False
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cd ./REUSE
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```
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## Inference
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Follow the simple steps below to generate enhanced speech using our model:
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1. Place your noisy speech files in the folder `noisy_audio/`
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