Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 from time import time
 import torch
 
-@st.cache(
+@st.cache_reesources(
     allow_output_mutation=True,
     hash_funcs={
         AutoTokenizer: lambda x: None,
@@ -65,7 +65,7 @@ st.markdown("""This is a demo for the Findings of EMNLP 2021 paper [REBEL: Relat
 
 lan = st.selectbox(
     'Select a Language',
-    ('ar', 'ca', 'de', 'el', 'en', 'es', 'fr', 'hi', 'it', 'ja', 'ko', 'nl', 'pl', 'pt', 'ru', 'sv', 'vi', 'zh'))
+    ('ar', 'ca', 'de', 'el', 'en', 'es', 'fr', 'hi', 'it', 'ja', 'ko', 'nl', 'pl', 'pt', 'ru', 'sv', 'vi', 'zh'), index=1)
 
 _Tokens = {'en': 'en_XX', 'de': 'de_DE', 'ca': 'ca_XX', 'ar': 'ar_AR', 'el': 'el_EL', 'it': 'it_IT', 'ja': 'ja_XX', 'ko': 'ko_KR', 'hi': 'hi_IN', 'pt': 'pt_XX', 'ru': 'ru_RU', 'pl': 'pl_PL', 'zh': 'zh_CN', 'fr': 'fr_XX', 'vi': 'vi_VN', 'sv':'sv_SE'}
 
@@ -73,11 +73,11 @@ tokenizer, model, dataset = load_models(lan)
 
 agree = st.checkbox('Free input', False)
 if agree:
-    text = st.text_input('Input text', 'Els Red Hot Chili Peppers es van formar a Los Angeles per Kiedis, Flea, el guitarrista Hillel Slovak i el bateria Jack Irons.')
+    text = st.text_input('Input text (current example in catalan)', 'Els Red Hot Chili Peppers es van formar a Los Angeles per Kiedis, Flea, el guitarrista Hillel Slovak i el bateria Jack Irons.')
     print(text)
 else:
     dataset_example = st.slider('dataset id', 0, 1000, 0)
-    text = dataset[dataset_example]['context']
+    text = dataset[dataset_example]['text']
 length_penalty = st.slider('length_penalty', 0, 10, 0)
 num_beams = st.slider('num_beams', 1, 20, 3)
 num_return_sequences = st.slider('num_return_sequences', 1, num_beams, 2)
@@ -105,8 +105,7 @@ st.write(text)
 
 if not agree:
     st.title('Silver output')
-    st.write(dataset[dataset_example]['triplets'])
-    st.write(extract_triplets_typed(dataset[dataset_example]['triplets']))
+    st.write(dataset[dataset_example]['relations'])
 
 st.title('Prediction text')
 decoded_preds = [text.replace('<s>', '').replace('</s>', '').replace('<pad>', '') for text in decoded_preds]