Create app.py

app.py

@@ -0,0 +1,51 @@
+import torch
+import torch.nn.functional as F
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+MODEL_PATH = "distilbert-imdb-chatbot"
+
+# Load model once
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
+model.eval()
+
+def analyze_review(review):
+    if review.strip() == "":
+        return "Please enter a movie review."
+
+    inputs = tokenizer(
+        review,
+        return_tensors="pt",
+        truncation=True,
+        padding=True,
+        max_length=256
+    )
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    probs = F.softmax(outputs.logits, dim=1)
+    confidence, prediction = torch.max(probs, dim=1)
+
+    sentiment = "Positive 😊" if prediction.item() == 1 else "Negative 😞"
+
+    return f"""
+🎬 **Sentiment:** {sentiment}  
+📊 **Confidence:** {confidence.item():.2f}
+"""
+
+# Gradio UI
+interface = gr.Interface(
+    fn=analyze_review,
+    inputs=gr.Textbox(
+        lines=4,
+        placeholder="Write a movie review here..."
+    ),
+    outputs="markdown",
+    title="🎬 Movie Review Chatbot",
+    description="DistilBERT fine-tuned on IMDB movie reviews"
+)
+
+if __name__ == "__main__":
+    interface.launch()