Update README.md

README.md

@@ -33,14 +33,36 @@ pip install speechbrain transformers
 Please notice that we encourage you to read our tutorials and learn more about
 [SpeechBrain](https://speechbrain.github.io).
 
+### Using the Vocoder with DiscreteSSL
 
-### Using the Vocoder
+```python
+import torch
+from speechbrain.lobes.models.huggingface_transformers.wavlm import (WavLM)
+
+inputs = torch.rand([3, 2000])
+model_hub = "microsoft/wavlm-large"
+save_path = "savedir"
+ssl_layer_num = [7,23]
+deduplicate =[False, True]
+bpe_tokenizers=[None, None]
+vocoder_repo_id = "speechbrain/hifigan-wavlm-k1000-LibriTTS"
+kmeans_dataset = "LibriSpeech"
+num_clusters = 1000
+ssl_model = WavLM(model_hub, save_path,output_all_hiddens=True)
+model = DiscreteSSL(save_path, ssl_model, vocoder_repo_id=vocoder_repo_id, kmeans_dataset=kmeans_dataset,num_clusters=num_clusters)
+tokens, _, _ = model.encode(inputs,SSL_layers=ssl_layer_num, deduplicates=deduplicate, bpe_tokenizers=bpe_tokenizers)
+sig = model.decode(tokens, ssl_layer_num)
+```
+
+
+
+### Standalone Vocoder Usage
 
 ```python
 import torch
 from speechbrain.inference.vocoders import UnitHIFIGAN
 
-hifi_gan_unit = UnitHIFIGAN.from_hparams(source="speechbrain/hifigan-wavlm-l1-3-7-12-18-23-k1000-LibriTTS", savedir="pretrained_models/vocoder")
+hifi_gan_unit = UnitHIFIGAN.from_hparams(source="speechbrain/hifigan-wavlm-k1000-LibriTTS", savedir="pretrained_models/vocoder")
 codes = torch.randint(0, 99, (100, 1))
 waveform = hifi_gan_unit.decode_unit(codes)