hf token

model.py

@@ -1,14 +1,14 @@
 import os
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
 from langchain_openai import OpenAI
-from huggingface_hub import login
-from dotenv import load_dotenv
+# from huggingface_hub import login
+# from dotenv import load_dotenv
 from logging import getLogger
 import streamlit as st
 import torch
 
 load_dotenv()
-# hf_token = os.environ.get("HF_TOKEN")
+hf_token = os.environ.get("HF_TOKEN")
 # # hf_token = st.secrets["HF_TOKEN"]
 # login(token=hf_token)
 logger = getLogger(__name__)
@@ -18,8 +18,14 @@ def get_local_model(model_name_or_path:str)->pipeline:
 
     #print(f"Model is running on {device}")
 
-    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
-    model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+    tokenizer = AutoTokenizer.from_pretrained(
+        model_name_or_path,
+        token = hf_token
+    )
+    model = AutoModelForSeq2SeqLM.from_pretrained(
+        model_name_or_path,
+        token = hf_token
+    )
     pipe = pipeline(
         task = 'summarization',
         model=model,