Update app.py

app.py

@@ -1,3 +1,24 @@
 import gradio as gr
+import torch
+from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
 
-gr.Interface.load("models/ashokurlana/mBART-TeSum").launch()
+description = "Telugu Abstractive Summarization"
+title = "TeSum"
+
+model = MBartForConditionalGeneration.from_pretrained("ashokurlana/mBART-TeSum")
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+model.eval()
+tokenizer = MBart50TokenizerFast.from_pretrained("ashokurlana/mBART-TeSum", src_lang="te_IN", tgt_lang="te_IN")
+
+def summarize(text):
+    model_inputs = tokenizer(src_text, return_tensors="pt")
+    with tokenizer.as_target_tokenizer():
+        labels = tokenizer(tgt_text, return_tensors="pt").input_ids
+    
+    return model(**model_inputs, labels=labels)
+
+interface = gr.Interface(transcribe, inputs='text', outputs='text')
+interface.launch(share=True)
+
+# gr.Interface.load("models/ashokurlana/mBART-TeSum").launch()