Duplicate from YatharthS/FlashSR

Co-authored-by: Yatharth Sharma <YatharthS@users.noreply.huggingface.co>

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README.md

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+---
+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.

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