Update app.py

app.py

@@ -8,11 +8,12 @@ import datasets
 # Load your fine-tuned model and tokenizer
 model_name = "google/flan-t5-large"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
-model.load_adapter("legacy107/adapter-flan-t5-large-bottleneck-adapter-cpgQA", source="hf")
-model.set_active_adapters("question_answering")
+peft_name = "checkiejan/flan-t5-prefix-25-9-2"
+peft_config = PeftConfig.from_pretrained(peft_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(peft_config.base_model_name_or_path)
+model = PeftModel.from_pretrained(model, peft_name)
 
-peft_name = "legacy107/flan-t5-large-ia3-bioasq-paraphrase"
+peft_name = "checkiejan/prefix-paraphase-50-19-auto"
 peft_config = PeftConfig.from_pretrained(peft_name)
 paraphrase_model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 paraphrase_model = PeftModel.from_pretrained(paraphrase_model, peft_name)