Update app.py

app.py

@@ -5,21 +5,24 @@ from transformers import T5Tokenizer, T5ForConditionalGeneration
 from transformers import pipeline
 import torch
 import base64
-import os
-from dotenv import load_dotenv
-load_dotenv()
-token = os.environ.get("HF_TOKEN")
+#import os
+#from dotenv import load_dotenv
+from huggingface_hub import HfApi
 
-# Use the token for model loading or other tasks
-tokenizer = T5Tokenizer.from_pretrained("LaMini-Flan-T5-248M", token=token)
+api = HfApi()
+token = api.get_secret("secret_token")  # Replace with your secret name
 
+#load_dotenv()
+#token = os.environ.get("HF_TOKEN")
 
 
-checkpoint = "D:/project/LaMini-Flan-T5-248M"
+
+
+checkpoint = "LaMini-Flan-T5-248M"
 #model and tokenizer loading
 
-tokenizer = T5Tokenizer.from_pretrained(checkpoint)
-base_model = T5ForConditionalGeneration.from_pretrained(checkpoint, device_map='auto', torch_dtype=torch.float32, offload_folder='D:/project/offload')
+tokenizer = T5Tokenizer.from_pretrained(checkpoint, token=token)
+base_model = T5ForConditionalGeneration.from_pretrained(checkpoint, token=token, device_map='auto', torch_dtype=torch.float32, offload_folder='D:/project/offload')
 
 #file loader and preprocessing
 def file_preprocessing(file):