asd

app.py

@@ -3,7 +3,7 @@ import json
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel
-from huggingface_hub import HfApi
+from huggingface_hub import HfApi, HfFolder
 import gradio as gr
 import time
 
@@ -23,8 +23,9 @@ def load_model_and_tokenizer():
         merged_model = AutoModelForCausalLM.from_pretrained(local_model_path)
     else:
         print("Downloading model from Hugging Face Hub...")
-        tokenizer = AutoTokenizer.from_pretrained(model_name)
-        merged_model = AutoModelForCausalLM.from_pretrained(model_name)
+        token = os.getenv("HF_AUTH_TOKEN")  # Ensure you set this environment variable with your Hugging Face token
+        tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=token)
+        merged_model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=token)
 
 def merge_models():
     print("Loading base model...")
@@ -56,10 +57,12 @@ def push_to_hub(repo_name):
     except Exception as e:
         print(f"Repository already exists or error occurred: {e}")
     
+    token = os.getenv("HF_AUTH_TOKEN")  # Ensure you set this environment variable with your Hugging Face token
     api.upload_folder(
         folder_path="merged_model",
         repo_id=repo_name,
         repo_type="model",
+        token=token
     )
     print("Model pushed successfully!")