Delete app_1.py

app_1.py

@@ -1,28 +0,0 @@
-import os
-import pandas as pd
-import streamlit as st
-HG_DIR = '/nlp/scr/msuzgun/cache_extra/huggingface'
-# Specify HG cache dirs -- currently use only for 2.7b model
-os.environ['TRANSFORMERS_CACHE'] = f'{HG_DIR}/transformers'
-os.environ['HF_HOME'] = HG_DIR
-
-## Import relevant libraries and dependencies
-#pip install datasets
-# Pretty print
-from pprint import pprint
-# Datasets load_dataset function
-from datasets import load_dataset
-# Transformers Autokenizer
-#from transformers import AutoTokenizer
-#tokenizer = AutoTokenizer.from_pretrained('distilbert-base-uncased')
-# Standard PyTorch DataLoader
-from torch.utils.data import DataLoader
-
-
-dataset_dict = load_dataset('HUPD/hupd',name='sample',data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather", cache_dir ='/u/scr/nlp/data/HUPD',icpr_label=None,train_filing_start_date='2016-01-01',train_filing_end_date='2016-01-31',val_filing_start_date='2017-01-01',val_filing_end_date='2017-01-31')
-
-df = pd.DataFrame.from_dict(dataset_dict["train"])
-
-# Create a DataFrame object from list
-df = pd.DataFrame(df,columns =['patent_number','decision', 'abstract', 'claims','filing_date'])
-st.dataframe(df)