Update app.py

app.py

@@ -35,14 +35,13 @@ def seed_everything(seed=42):
 seed_everything(seed=CFG.seed) 
 
 
-st.json(CFG.input_data)
 tokenizer = AutoTokenizer.from_pretrained(CFG.model_name_or_path, return_tensors='pt')
     
 if CFG.model == 't5':
     model = AutoModelForSeq2SeqLM.from_pretrained(CFG.model_name_or_path).to(device)
 elif CFG.model == 'deberta':
     model = EncoderDecoderModel.from_pretrained(CFG.model_name_or_path).to(device)
-print('ok')
+
 input_compound = CFG.input_data
 min_length = min(input_compound.find('CATALYST') - input_compound.find(':') - 10, 0)
 inp = tokenizer(input_compound, return_tensors='pt').to(device)
@@ -61,4 +60,4 @@ if type(mol) == None:
 output += scores
 output = [input_compound] + output
 output_df = pd.DataFrame(np.array(output).reshape(1, -1), columns=['input'] + [f'{i}th' for i in range(CFG.num_beams)] + ['valid compound'] + [f'{i}th score' for i in range(CFG.num_beams)] + ['valid compound score'])
-st.json(output)
+st.table(output_df)