Fix merged changes

app.py

@@ -1,15 +1,10 @@
 import streamlit as st
-<<<<<<< HEAD
-from datasets import load_dataset, Features, Value, Sequence
-=======
 from datasets import load_dataset
->>>>>>> 81414ba96ac55f927033c62ee5c2db6c6a22349c
 from transformers import DistilBertForSequenceClassification, DistilBertTokenizer
 
 decision_to_str = {'REJECTED': 0, 'ACCEPTED': 1, 'PENDING': 2, 'CONT-REJECTED': 3, 'CONT-ACCEPTED': 4, 'CONT-PENDING': 5}
 
 dataset_dict = load_dataset('HUPD/hupd',
-<<<<<<< HEAD
     name='sample',
     data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather", 
     icpr_label=None,
@@ -26,25 +21,6 @@ tokenizer_abstract = DistilBertTokenizer.from_pretrained('theresatvan/hupd-disti
 
 model_claims = DistilBertForSequenceClassification.from_pretrained('theresatvan/hupd-distilbert-claims')
 tokenizer_claims = DistilBertTokenizer.from_pretrained('theresatvan/hupd-distilbert-claims')
-=======
-    name='all',
-    data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather", 
-    icpr_label=None,
-    force_extract=True,
-    train_filing_start_date='2016-01-01',
-    train_filing_end_date='2016-01-01',
-    val_filing_start_date='2017-01-01',
-    val_filing_end_date='2017-05-31',
-)
-
-dataset = dataset_dict['validation'].filter(lambda e: e['decision'] in ['REJECTED', 'ACCEPTED'])
-
-model_abstract = DistilBertForSequenceClassification('theresatvan/hupd-distilbert-abstract')
-tokenizer_abstract = DistilBertTokenizer('theresatvan/hupd-distilbert-abstract')
-
-model_claims = DistilBertForSequenceClassification('theresatvan/hupd-distilbert-claims')
-tokenizer_claims = DistilBertTokenizer('theresatvan/hupd-distilbert-claims')
->>>>>>> 81414ba96ac55f927033c62ee5c2db6c6a22349c
 
 
 def predict(model_abstract, model_claims, tokenizer_abstract, tokenizer_claims, input):
@@ -75,21 +51,13 @@ if __name__ == '__main__':
     st.title = "Can I Patent This?"
     
     form = st.form('patent-prediction-form')
-<<<<<<< HEAD
     dropdown = [example['application_number'] for example in dataset]
-=======
-    dropdown = []
->>>>>>> 81414ba96ac55f927033c62ee5c2db6c6a22349c
     
     input_application = form.selectbox('Select a patent\'s application number', patents_dropdown)
     submit = form.form_submit_button("Submit")
     
     if submit:
-<<<<<<< HEAD
         input = dataset.filter(lambda e: e['patent_number'] == input_application)
-=======
-        input = dataset.filter(lambda e: e['application_number'] == input_application)
->>>>>>> 81414ba96ac55f927033c62ee5c2db6c6a22349c
         
         label, prob = predict(model_abstract, model_claims, tokenizer_abstract, tokenizer_claims, input)