Code Updated

app.py

@@ -1,6 +1,11 @@
 import streamlit as st
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer
 from datasets import load_dataset
+from huggingface_hub import login
+
+# Authenticate to Hugging Face
+hugging_face_token = "your_hugging_face_api_token"  # Replace with your actual token
+login(hugging_face_token)
 
 # Load the dataset
 ds = load_dataset("Vezora/Open-Critic-GPT")
@@ -9,7 +14,7 @@ st.write("Dataset")
 
 # Load the model and tokenizer
 model_name = "meta-llama/Meta-Llama-3-8B"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 # Function to generate a response from the model