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README.md

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 license: mit
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+
+# Amphion Vocoder Pretrained Models
+
+We provide a [DiffWave](https://github.com/open-mmlab/Amphion/tree/main/egs/vocoder/diffusion) pretrained checkpoint, which is trained on 125 hours of speech data and 80 hours of singing voice data.
+
+## Quick Start
+
+To utilize these pretrained vocoders, just run the following commands:
+
+### Step1: Download the checkpoint
+```bash
+git lfs install
+git clone https://huggingface.co/amphion/diffwave
+```
+
+### Step2: Clone the Amphion's Source Code of GitHub
+```bash
+git clone https://github.com/open-mmlab/Amphion.git
+```
+
+### Step3: Specify the checkpoint's path
+Use the soft link to specify the downloaded checkpoint in the first step:
+
+```bash
+cd Amphion
+mkdir -p ckpts/vocoder
+ln -s "$(realpath ../diffwave/diffwave)" pretrained/diffwave
+```
+
+### Step4: Inference
+For analysis synthesis on the processed dataset, raw waveform, or predicted mel spectrograms, you can follow the inference part of [this recipe](https://github.com/open-mmlab/Amphion/tree/main/egs/vocoder/diffusion).
+
+```bash
+sh egs/vocoder/diffusion/diffwave/run.sh --stage 3 \
+	--infer_mode [Your chosen inference mode] \
+	--infer_datasets [Datasets you want to inference, needed when infer_from_dataset] \
+	--infer_feature_dir [Your path to your predicted acoustic features, needed when infer_from_feature] \
+	--infer_audio_dir [Your path to your audio files, needed when infer_form_audio] \
+	--infer_expt_dir Amphion/ckpts/vocoder/[YourExptName] \
+	--infer_output_dir Amphion/ckpts/vocoder/[YourExptName]/result \
+```