Update README.md

README.md

@@ -29,7 +29,22 @@ ECAPA2 is a hybrid neural network architecture and training strategy for speaker
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
-## Uses
+## How-to-use
+
+Extracting speaker embeddings is easy and only requires a few lines of code:
+```
+audio = torchaudio.load('sample.wav')
+ecapa2_model = torch.load('model.pt')
+embedding = ecapa2_model.extract_embedding(audio)
+```
+
+For the extraction of other hierachical features, a separate model function is provided:
+```
+feature = ecapa2_model.extract_feature(label='gfe1')
+```
+
+The list of available labels exists of: 'lfe1', 'lfe2', 'lfe3', 'lfe4', 'gfe1', 'gfe2', 'pool' and 'embedding' (equal to model.extract_embedding()).
+
 
 <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->