Update app.py

app.py

@@ -1,21 +1,21 @@
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, AutoModelForSequenceClassification
 from peft import PeftModel  # Ensure PEFT is installed: pip install peft
 import os
 
 # Define the model and base paths
-model = "FadQ/gemma-2b-diary-consultaton-chatbot"
-# base_model = "google/gemma-2b"
+model_path = "FadQ/gemma-2b-diary-consultaton-chatbot"
+base_model = "google/gemma-2b"
 
-# # Use your Hugging Face token
-# hf_token = os.getenv('HF_TOKEN')
+# Use your Hugging Face token
+hf_token = os.getenv('HF_TOKEN')
 
-# # Load tokenizer with authentication
-# tokenizer = AutoTokenizer.from_pretrained(base_model, token=hf_token, force_download=True)
+# Load tokenizer with authentication
+tokenizer = AutoTokenizer.from_pretrained(base_model, token=hf_token, force_download=True)
 
-# # Load the base model and apply adapter with authentication
-# base_model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto", token=hf_token)
-# model = PeftModel.from_pretrained(base_model, model_path)
+# Load the base model and apply adapter with authentication
+base_model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto", token=hf_token)
+model = PeftModel.from_pretrained(base_model, model_path)
 
 
 # Create pipeline