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Merge pull request #2 from NVIDIA/local_gradio_demo
integrate local gradio demo
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README.md

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## BigVGAN: A Universal Neural Vocoder with Large-Scale Training
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/bigvgan-a-universal-neural-vocoder-with-large/speech-synthesis-on-libritts)](https://paperswithcode.com/sota/speech-synthesis-on-libritts?p=bigvgan-a-universal-neural-vocoder-with-large)
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#### Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon
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<center><img src="https://user-images.githubusercontent.com/15963413/218609148-881e39df-33af-4af9-ab95-1427c4ebf062.png" width="800"></center>
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## News
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[Jul 2024 (v2.2)] The repository now includes an interactive local demo using gradio.
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[Jul 2024 (v2.1)] BigVGAN is now integrated with 🤗 Hugging Face Hub with easy access to inference using pretrained checkpoints. We also provide an interactive demo on Hugging Face Spaces.
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[Jul 2024 (v2)] We release BigVGAN-v2 along with pretrained checkpoints. Below are the highlights:
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wav_gen_int16 = (wav_gen_float * 32767.0).numpy().astype('int16') # wav_gen is now np.ndarray with shape [1, T_time] and int16 dtype
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```
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## Local gradio demo <a href='https://github.com/gradio-app/gradio'><img src='https://img.shields.io/github/stars/gradio-app/gradio'></a>
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You can run a local gradio demo using below command:
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```python
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pip install -r gradio_demo/requirements.txt
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python gradio_demo/app.py
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```
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## Training
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Create symbolic link to the root of the dataset. The codebase uses filelist with the relative path from the dataset. Below are the example commands for LibriTTS dataset:
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``` shell

gradio_demo/__init__.py

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