Update app.py

app.py

@@ -4,13 +4,18 @@ import gradio as gr
 import streamlit as st
 from transformers import pipeline
 from datasets import load_dataset
+from huggingface_hub import hf_hub_download
+from datasets import load_dataset
+
+file_path = hf_hub_download("BEE-spoke-data/survivorslib-law-books", filename="train.parquet")
+ds = load_dataset("parquet", data_files=file_path)
 
 # Initialize text-generation pipeline with the model
 model_name = "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
 pipe = pipeline("text-generation", model=model_name)
 
 # Load the dataset from the cloned local directory
-ds = load_dataset("./canadian-legal-data", split="train",verify=False)
+# ds = load_dataset("./canadian-legal-data", split="train",verify=False)
 
 # Gradio Interface setup
 def respond(