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FlashSR

FlashSR is a 2MB audio super-resolution model based on the HierSpeech++'s upsampler architecture. It upscales 16kHz audio to 48kHz at speeds ranging from 200x to 400x real-time.

TypeOtherVersionRevision 3e19cc9BClasse

Source du modèle

Type
Other
Taille du fichier
487 KB–1,64 MB
Version
vRevision 3e19cc9
Mis à jour
26 sept. 2026
Téléchargements
0
Source
Hugging Face

Description de la source

FlashSR

FlashSR is a 2MB audio super-resolution model based on the HierSpeech++'s upsampler architecture. It upscales 16kHz audio to 48kHz at speeds ranging from 200x to 400x real-time.

Details

  • Model Size: 2MB for pytorch version, 500KB for onnx version
  • Input Rate: 16kHz
  • Output Rate: 48kHz
  • Inference Speed: 200x - 400x real-time depending on gpu and dtype

Performance Summary

FlashSR is designed for high-speed frequency reconstruction. It offers a significantly lower computational footprint compared to alternatives such as Resemble-Enhance and ClearerVoice, while maintaining similar output quality.

Benchmark Comparison

ModelSpeedSize
FlashSR200x - 400x realtime2MB/500KB
Resemble-Enhance< 20x realtime~700MB+
ClearerVoice< 20x realtime~200MB+

Usage

Usage instructions for onnx/pytorch and source code are available on GitHub: https://github.com/ysharma3501/FlashSR

Credits

Thanks to the authors of HierSpeech++ as this was based on it's 48khz upsampler and Xenova for onnx code.

Sources

1 source
Hugging FacePrincipalVersion 3e19cc92e655c2e0661e6268efdade60f42fd0b8
huggingface.co/YatharthS/FlashSR/tree/3e19cc92e655c2e0661e6268efdade60f42fd0b8

Vérifié 29 août

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Artefacts du modèle

2 artefacts

onnx/model.onnx

onnx · 487 KB · SHA-256 e255c76b227f…0c7a · Hugging Face

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upsampler.pth

pth · 1,64 MB · SHA-256 62c70874ac4e…eefc · Hugging Face

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Extraits de sources

2 extraits

--- license: apache-2.0 pipeline_tag: audio-to-audio tags: - pytorch - audio - upsampling --- # FlashSR FlashSR is a 2MB audio super-resolution model based on the HierSpeech++'s upsampler architecture. It upscales 16kHz audio to 48kHz at speeds ranging from 200x to 400x real-time. ### Details * **Model Size:** 2MB for pytorch version, 500KB for onnx version * **Input Rate:** 16kHz * **Output Rate:** 48kHz * **Inference Speed:** 200x - 400x real-time depending on gpu and dtype ### Performance Summary FlashSR is designed for high-speed frequency reconstruction. It offers a significantly lower computational footprint compared to alternatives such as Resemble-Enhance and ClearerVoice, while maintaining similar output quality. ### Benchmark Comparison | Model | Speed | Size | | :--- | :--- | :--- | | **FlashSR** | **200x - 400x realtime** | **2MB/500KB** | | Resemble-Enhance | < 20x realtime | ~700MB+ | | ClearerVoice | < 20x realtime | ~200MB+ | ### Usage Usage instructions for onnx/pytorch and source code are available on GitHub: https://github.com/ysharma3501/FlashSR ### Credits Thanks to the authors of **HierSpeech++** as this was based on it's 48khz upsampler and [Xenova](https://github.com/xenova/) for onnx code.

Source context: 0 downloads · 65 likes · Pipeline audio-to-audio · Repo YatharthS/FlashSR