Update app.py

app.py

@@ -1,7 +1,26 @@
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+import torch.nn.functional as F
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load the model and tokenizer
+model_name = "tabularisai/multilingual-sentiment-analysis"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+# Define labels
+labels = ["Negative", "Neutral", "Positive"]
+
+# Define inference function
+def analyze_sentiment(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = F.softmax(outputs.logits, dim=1)
+        confidence, predicted_class = torch.max(probs, dim=1)
+        label = labels[predicted_class.item()]
+        return f"{label} ({confidence.item():.2%} confidence)"
+
+# Gradio interface
+demo = gr.Interface(fn=analyze_sentiment, inputs="text", outputs="text")
 demo.launch()