Create app.py

app.py

@@ -0,0 +1,42 @@
+import torch
+import gradio as gr
+from transformers import (
+    AutoTokenizer,
+    AutoModelForSequenceClassification
+)
+
+MODEL_NAME = "duclo90/results"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
+
+model.eval()
+
+def classify_text(text):
+    inputs = tokenizer(
+        text,
+        return_tensors="pt",
+        truncation=True,
+        max_length=512
+    )
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.softmax(outputs.logits, dim=-1)
+        score, pred = torch.max(probs, dim=-1)
+
+    label = model.config.id2label[pred.item()]
+    confidence = round(score.item(), 3)
+
+    return f"Prediction: {label} (Confidence: {confidence})"
+
+
+iface = gr.Interface(
+    fn=classify_text,
+    inputs=gr.Textbox(lines=6, placeholder="Enter text here..."),
+    outputs="text",
+    title="Human vs Machine Text Classifier",
+    description="Classifies text as human-written or machine-generated using a fine-tuned BERT model."
+)
+
+iface.launch()