Update app.py

app.py

@@ -1,22 +1,22 @@
-import gradio as gr
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-import torch
-
-model_path = "./models/fine_tuned_xlm_roberta_quantized"
-model = AutoModelForSequenceClassification.from_pretrained(model_path)
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-
-def classify_text(text):
-    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
-    outputs = model(**inputs)
-    prediction = torch.argmax(outputs.logits, dim=1).item()
-    label = "Correct" if prediction == 1 else "Incorrect"
-    return label
-
-iface = gr.Interface(fn=classify_text, 
-                     inputs="text", 
-                     outputs="text",
-                     title="Multi-Language RL Text Classifier")
-
-if __name__ == "__main__":
-    iface.launch()
+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+model_path = "SivaMallikarjun/multi-language-rl-model"
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+def classify_text(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    outputs = model(**inputs)
+    prediction = torch.argmax(outputs.logits, dim=1).item()
+    label = "Correct" if prediction == 1 else "Incorrect"
+    return label
+
+iface = gr.Interface(fn=classify_text, 
+                     inputs="text", 
+                     outputs="text",
+                     title="Multi-Language RL Text Classifier")
+
+if __name__ == "__main__":
+    iface.launch()