Update README.md

README.md

@@ -40,23 +40,43 @@ For the MMS project, a separate VITS checkpoint is trained on each langauge.
 
 ## Usage
 
-Using this checkpoint from Hugging Face Transformers:
+MMS-TTS is available in the 🤗 Transformers library from version 4.33 onwards. To use this checkpoint, 
+first install the latest version of the library:
+
+```
+pip install --upgrade transformers accelerate
+```
+
+Then, run inference with the following code-snippet:
 
 ```python
 from transformers import VitsModel, AutoTokenizer
 import torch
 
-model = VitsModel.from_pretrained("Matthijs/mms-tts-eng")
-tokenizer = AutoTokenizer.from_pretrained("Matthijs/mms-tts-eng")
+model = VitsModel.from_pretrained("facebook/mms-tts-eng")
+tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-eng")
 
 text = "Hey, it's Hugging Face on the phone"
 inputs = tokenizer(text, return_tensors="pt")
 
 with torch.no_grad():
     output = model(**inputs).waveform
+```
+
+The resulting waveform can be saved as a `.wav` file:
 
+```python
+import scipy
+
+scipy.io.wavfile.write("techno.wav", rate=model.config.sampling_rate, data=output)
+```
+
+Or displayed in a Jupyter Notebook / Google Colab:
+
+```python
 from IPython.display import Audio
-Audio(output[0], rate=16000)
+
+Audio(output, rate=model.config.sampling_rate)
 ```
 
 ## BibTex citation