Update app.py

app.py

@@ -7,20 +7,19 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.vectorstores import FAISS
 from langchain.memory import ConversationBufferMemory
 from langchain_community.document_loaders import PyPDFLoader
-from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import pipeline, T5Tokenizer, T5ForConditionalGeneration
 import torch
 from transformers import pipeline
 import os
 import tempfile
 
-model = AutoModelForSeq2SeqLM.from_pretrained("LaMini-Flan-T5-783M")
-tokenizer = AutoTokenizer.from_pretrained("LaMini-Flan-T5-783M", device_map = 'auto')
+#model = AutoModelForSeq2SeqLM.from_pretrained("LaMini-Flan-T5-783M")
+#tokenizer = AutoTokenizer.from_pretrained("LaMini-Flan-T5-783M", device_map = 'auto')
 
 
 checkpoint = "LaMini-Flan-T5-783M"
-#tokenizer = T5Tokenizer.from_pretrained(checkpoint)
-
-#base_model = T5ForConditionalGeneration.from_pretrained( checkpoint, device_map = 'auto', torch_dtype = torch.float32 )
+tokenizer = T5Tokenizer.from_pretrained(checkpoint)
+base_model = T5ForConditionalGeneration.from_pretrained( checkpoint, device_map = 'auto', torch_dtype = torch.float32 )
 
 def llm_pipeline():
     pipe = pipeline(
@@ -58,6 +57,7 @@ def display_chat_history(chain):
         with st.form(key='my_form', clear_on_submit=True):
             user_input = st.text_input("Question:", placeholder="Ask about your PDF", key='input')
             submit_button = st.form_submit_button(label='Send')
+            
 
         if submit_button and user_input:
             with st.spinner('Generating response...'):