change probs

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from transformers import AutoTokenizer
 import torch
+import pandas as pd
 import matplotlib.pyplot as plt
 from model import EnergySmellsDetector
 from config import SMELLS, BEST_THRESHOLD
@@ -12,8 +13,7 @@ model = EnergySmellsDetector.load_model_from_hf()
 def get_predictions(code_snippet):
     inputs = tokenizer(code_snippet, return_tensors="pt", truncation=True)
     with torch.no_grad():
-        logits = model(**inputs)[0]
-        probs = torch.sigmoid(logits).cpu().numpy().flatten()
+        probs = model(**inputs)[0].cpu().numpy().flatten()  # Model output is already sigmoid applied
         rounded_logits = (probs > BEST_THRESHOLD).astype(int)
 
     # Prepare results in a dictionary