Replaced Auto with T5 instances

app.py

@@ -1,12 +1,12 @@
 import gradio as gr
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
+from transformers import T5Tokenizer, T5ForConditionalGeneration, AutoModelForCausalLM, AutoTokenizer, T5Config
 
 # Load the model and tokenizer from Hugging Face Spaces
 model_name = "currentlyexhausted/flan-t5-summarizer"  # update with your model name
-config = AutoConfig.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, config=config)
+config = T5Config.from_pretrained(model_name)
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name, config=config)
 
 # Define the function to generate summary
 def generate_summary(passage):