Update README.md

README.md

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 ---
 license: apache-2.0
 ---
+
+This model is trained on Google's AudioSet (28GB data) for 1 million steps. (Originally planned 2 million steps, but I'm exploring better training schedule)
+
+You can regard it as a pretrained base model, which is common in language models but not for vocoders.
+
+How to load and use this model:
+
+```python
+import torch
+import torchaudio
+from scipy.io.wavfile import write
+with torch.no_grad():
+  from vocos import Vocos
+  A = torch.load("./vocos_checkpoint_epoch=464_step=1001610_val_loss=7.1732.ckpt", map_location="cpu")
+  V = Vocos.from_hparams("./config.yaml")
+  V.load_state_dict(A['state_dict'], strict=False)
+  V.eval()
+  def safe_log(x: torch.Tensor, clip_val: float = 1e-7):
+    return torch.log(torch.clip(x, min=clip_val))
+  voice, sr = torchaudio.load('example.wav') # must be sample_rate=32000
+  if sr != 32000:
+    raise ValueError
+  mel = torchaudio.transforms.MelSpectrogram(
+              sample_rate=32000, n_fft=2048, hop_length=1024, n_mels=128, center=True, power=1,
+          )(voice)
+  mel = safe_log(mel)
+  audio = V.decode(mel)
+write('out.wav', 32000, audio.flatten().numpy())
+```
+
+