Update README.md

README.md

@@ -29,6 +29,7 @@ to build the architecture of the model.
 Its weights are then downloaded from this repository.
 ```
 from spk_embeddings import EmbeddingsModel, compute_embedding
+import torch
 
 nt_extractor = EmbeddingsModel.from_pretrained("orange/w-pro")
 nt_extractor.eval()
@@ -50,6 +51,8 @@ wav2 = "/voxceleb1_2019/test/wav/id10270/8jEAjG6SegY/00008.wav"
 e1 = compute_embedding(wav1, nt_extractor)
 e2 = compute_embedding(wav2, nt_extractor)
 sim = float(torch.matmul(e1,e2.t()))
+
+print(sim) #0.5393530130386353
 ```
 
 # Evaluations