Update app.py

app.py

@@ -2,19 +2,14 @@ import torch
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-# Hugging Face model repo
 MODEL_NAME = "duclo90/Semeval"
 
-# Load tokenizer and model explicitly
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
-
-# Put model in eval mode
 model.eval()
 
-# Inference function
 def classify_text(text):
-    if not text or text.strip() == "":
+    if not text.strip():
         return "Please enter some text."
 
     inputs = tokenizer(
@@ -26,8 +21,7 @@ def classify_text(text):
     )
 
     with torch.no_grad():
-        outputs = model(**inputs)
-        logits = outputs.logits
+        logits = model(**inputs).logits
 
     probs = torch.softmax(logits, dim=-1)
     pred_id = torch.argmax(probs, dim=1).item()
@@ -37,17 +31,11 @@ def classify_text(text):
 
     return f"Prediction: {label} (Confidence: {confidence})"
 
-# Gradio UI
 iface = gr.Interface(
     fn=classify_text,
-    inputs=gr.Textbox(
-        lines=6,
-        placeholder="Enter text here..."
-    ),
+    inputs=gr.Textbox(lines=6),
     outputs="text",
     title="Human vs Machine Text Classifier",
-    description="Detect whether a text is written by a human or generated by a machine."
 )
 
-# Launch app
 iface.launch()