Update chatbot.py

chatbot.py

@@ -6,6 +6,7 @@ import langchain.globals
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import streamlit as st
 from langchain_community.llms import HuggingFaceHub
+from transformers import pipeline
 
 my_model_id = os.getenv('MODEL_REPO_ID', 'Default Value')
 token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
@@ -14,18 +15,15 @@ token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
 def load_model():
     #tokenizer = AutoTokenizer.from_pretrained("KvrParaskevi/Hotel-Assistant-Attempt4-Llama-2-7b")
     #model = AutoModelForCausalLM.from_pretrained("KvrParaskevi/Hotel-Assistant-Attempt4-Llama-2-7b")
-    model = HuggingFaceHub(
-        repo_id=my_model_id,
-        task="text-generation",
-        model_kwargs={
-            "max_new_tokens": 512,
-            "top_k": 30,
-            "temperature": 0.1,
-            "repetition_penalty": 1.03,
-        },
-        huggingfacehub_api_token = token,
-    )
-    return model
+    
+    # Replace 'username/model_name' with your model's identifier on the Hugging Face Model Hub
+    model_identifier = "KvrParaskevi/Hotel-Assistant-Attempt4-Llama-2-7b"
+    task = "text-classification"  # Change this to your model's task
+    
+    # Load the model using the pipeline
+    model_pipeline = pipeline(task, model=model_identifier)
+
+    return model_pipeline
 
 def demo_miny_memory(model):
     # llm_data = get_Model(hugging_face_key)