Update app.py

app.py

@@ -3,8 +3,7 @@ from langchain_core.prompts import ChatPromptTemplate, HumanMessagePromptTemplat
 from langchain.schema import SystemMessage
 import streamlit as st
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-from transformers.models.llama import LlamaTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, LlamaForCausalLM, LlamaTokenizer
 from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
 import nltk
 import json
@@ -47,8 +46,8 @@ if dataset_file:
     df = pd.read_csv(dataset_file)
 
 # Initialize tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True) or LlamaTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=HF_TOKEN, use_fast=True) or LlamaTokenizer.from_pretrained(model_name, use_auth_token=HF_TOKEN, use_fast=True)
+model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=HF_TOKEN) or LlamaForCausalLM.from_pretrained(model_name, use_auth_token=HF_TOKEN)
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, return_full_text=True)
 llm = HuggingFacePipeline(pipeline=pipe)