added predictors

ArtistCoherencyModel.py

@@ -43,7 +43,7 @@ class ArtistCoherencyModel(nn.Module, PyTorchModelHubMixin):
     def predict_artist(self, song: str) -> tuple[str, float]:
         logits = F.softmax(self.generate_artist_logits(song)[0], dim=0)
         predicted_class_id = logits.argmax().item()
-        return self.artist_model.config.id2label[predicted_class_id], float(
+        return self.artist_model.config.id2label[predicted_class_id], 100 * float(
             logits[predicted_class_id]
         )
 
@@ -57,7 +57,7 @@ class ArtistCoherencyModel(nn.Module, PyTorchModelHubMixin):
     def predict_coherency(self, song: str) -> tuple[str, float]:
         logits = F.softmax(self.generate_coherency_logits(song)[0], dim=0)
         predicted_class_id = logits.argmax().item()
-        return self.coherency_model.config.id2label[predicted_class_id], float(
+        return self.coherency_model.config.id2label[predicted_class_id], 100 * float(
             logits[predicted_class_id]
         )