Created utils.py

utils.py

@@ -0,0 +1,19 @@
+def model_predict(model, tokenizer, sentences):
+    """
+    Predict the labels of the sentences using the model and tokenizer
+    Args:
+        model: Model (transformers)
+        tokenizer: Tokenizer (transformers tokenizer)
+        sentences: Sentences to predict (ndarray)
+    Returns:
+        predictions: Predicted labels
+    """
+
+
+    inputs = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt", max_length=512).to(device)
+    # Classify sentences
+    with torch.no_grad():
+        outputs = model(**inputs) # get the logits
+        label = np.argmax(outputs.logits.to("cpu"))
+        
+    return str(labels)