Update app.py

app.py

@@ -11,7 +11,7 @@ text = st.text_input('Enter text')
 
 # out = model()
 
-model = AutoModelForSequenceClassification.from_pretrained("./bert-finetuned-sem_eval-english/checkpoint-36819")
+model = AutoModelForSequenceClassification.from_pretrained("./checkpoint-36819")
 # model.to('cuda')
 
 if st.button("Predict"):
@@ -23,10 +23,8 @@ if st.button("Predict"):
     utility = Utility()
     id2label, label2id, tokenizer, tokenized_plot = utility.tokenize(clean_plot, ["Action","Drama", "Romance", "Comedy", "Thriller"])
     st.write(tokenized_plot)
-    # xtrain_input_ids = [np.asarray(xtrain[i]['input_ids']) for i in range(xtrain.shape[0])]
-    # xtrain_attention_mask = [np.asarray(xtrain[i]['attention_mask']) for i in range(xtrain.shape[0])]
-    # xval_input_ids = [np.asarray(xval[i]['input_ids']) for i in range(xval.shape[0])]
-    # xval_attention_mask = [np.asarray(xval[i]['attention_mask']) for i in range(xval.shape[0])]
+    xtrain_input_ids = [np.asarray(tokenized_plot['input_ids'])]
+    xtrain_attention_mask = [np.asarray(tokenized_plot['attention_mask'])]
     st.write([np.asarray(tokenized_plot['input_ids'])])
     st.write(clean_plot)