made some changes 2

Components/model_Responce.py

@@ -54,15 +54,9 @@ def model_prediction(text, model=model, tokenizer=tokenizer, labels=outcome_labe
     # Hugging face model
     # Tokenize the text
     inputs = tokenizer(text, return_tensors="pt")
-    # Forward pass through the model
-    with torch.no_grad():
-        outputs = model(**inputs)
+    outputs = model(inputs)
     
     # Get the predicted class probabilities
-    # probs = outputs.logits.softmax(dim=-1)
-        # Get predicted probabilities and labels
-    probabilities = torch.nn.functional.softmax(outputs.logits, dim=1).numpy()[0]
-    predicted_label_index = np.argmax(probabilities)
-    predicted_label = labels[predicted_label_index]
+    probs = outputs.logits.softmax(dim=-1)
 
-    return predicted_label
+    return labels[torch.argmax(probs)]