Update app.py

app.py

@@ -1,33 +1,53 @@
-# Install dependencies if not already installed
-# !pip install transformers gradio
-
-from transformers import pipeline
+import torch
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-# Load your model and tokenizer from Hugging Face
-model_name = "duclo90/Semeval"  # replace with your HF repo
+# Hugging Face model repo
+MODEL_NAME = "duclo90/Semeval"
 
-classifier = pipeline(
-    "text-classification",
-    model=model_name,
-    tokenizer=model_name
-)
+# Load tokenizer and model explicitly
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
 
-# Function to classify text
+# Put model in eval mode
+model.eval()
+
+# Inference function
 def classify_text(text):
-    result = classifier(text)
-    label = result[0]['label']
-    score = round(result[0]['score'], 3)
-    return f"Prediction: {label} (Confidence: {score})"
+    if not text or text.strip() == "":
+        return "Please enter some text."
+
+    inputs = tokenizer(
+        text,
+        return_tensors="pt",
+        truncation=True,
+        padding=True,
+        max_length=512,
+    )
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+
+    probs = torch.softmax(logits, dim=-1)
+    pred_id = torch.argmax(probs, dim=1).item()
+
+    label = model.config.id2label[pred_id]
+    confidence = round(probs[0][pred_id].item(), 3)
+
+    return f"Prediction: {label} (Confidence: {confidence})"
 
-# Create Gradio interface
+# Gradio UI
 iface = gr.Interface(
     fn=classify_text,
-    inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
+    inputs=gr.Textbox(
+        lines=6,
+        placeholder="Enter text here..."
+    ),
     outputs="text",
     title="Human vs Machine Text Classifier",
-    description="Enter text and the model will predict if it was written by a human or generated by a machine."
+    description="Detect whether a text is written by a human or generated by a machine."
 )
 
-# Launch the web app
-iface.launch(share=True)  # share=True generates a public link
+# Launch app
+iface.launch()