use loading spinner while downloading datasets

app.py

@@ -1,22 +1,23 @@
 import streamlit as st
 from transformers import pipeline
-from datasets import load_dataset, Dataset, DatasetDict
+from datasets import load_dataset
 
 # load the dataset and
 # use the patent number, abstract and claim columns for UI
-dataset_dict = load_dataset(
-    "HUPD/hupd",
-    name="sample",
-    data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather",
-    icpr_label=None,
-    train_filing_start_date="2016-01-01",
-    train_filing_end_date="2016-01-21",
-    val_filing_start_date="2016-01-22",
-    val_filing_end_date="2016-01-31",
-)
+with st.spinner("Setting up the app..."):
+    dataset_dict = load_dataset(
+        "HUPD/hupd",
+        name="sample",
+        data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather",
+        icpr_label=None,
+        train_filing_start_date="2016-01-01",
+        train_filing_end_date="2016-01-21",
+        val_filing_start_date="2016-01-22",
+        val_filing_end_date="2016-01-31",
+    )
 
-# widget for selecting our finetuned langugae model
-language_model_path = "juliaannjose/finetuned_model"
+    # widget for selecting our finetuned langugae model
+    language_model_path = "juliaannjose/finetuned_model"
 
 # pass the model to transformers pipeline - model selection component.
 classifier_model = pipeline(model=language_model_path)