Update README.md

README.md

@@ -54,12 +54,11 @@ def speech_file_to_array_fn(path, sampling_rate):
 
 def predict(path, sampling_rate):
     speech = speech_file_to_array_fn(path, sampling_rate)
-    features = feature_extractor(speech, sampling_rate=sampling_rate, return_tensors="pt", padding=True)
-
-    input_values = features.input_values.to(device)
+    inputs = feature_extractor(speech, sampling_rate=sampling_rate, return_tensors="pt", padding=True)
+    inputs = {key: inputs[key].to(device) for key in inputs}
 
     with torch.no_grad():
-        logits = model(input_values).logits
+        logits = model(**inputs).logits
 
     scores = F.softmax(logits, dim=1).detach().cpu().numpy()[0]
     outputs = [{"Label": config.id2label[i], "Score": f"{round(score * 100, 3):.1f}%"} for i, score in enumerate(scores)]