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app.py

@@ -5,13 +5,14 @@ model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
 tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base")
 
 def index(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt")
+    # Truncate or split the input sequence to fit within the model's maximum sequence length
+    inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
     outputs = model.generate(**inputs)
 
-    print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
-
-    return tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    decoded_outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    print(decoded_outputs)
 
+    return decoded_outputs
 
 inputs_image_url = [
     gr.Textbox(type="text", label="Topic Name"),
@@ -32,4 +33,4 @@ interface_image_url = gr.Interface(
 gr.TabbedInterface(
     [interface_image_url],
     tab_names=['Some inference']
-).queue().launch()
+).launch()