Update app.py

app.py

@@ -3,7 +3,7 @@ from transformers import BertConfig, BertForSequenceClassification, AutoTokenize
 from safetensors import safe_open
 import torch
 
-config_path = "modelbert2/config.json"
+config_path = "peterkros/cofogv1-bert/modelbert2/config.json"
 config = BertConfig.from_json_file(config_path)
 model = BertForSequenceClassification(config)
 
@@ -12,11 +12,11 @@ model_path = "modelbert2"
 model = BertForSequenceClassification.from_pretrained(model_path)
 tokenizer = AutoTokenizer.from_pretrained(model_path)
 
-tokenizer = AutoTokenizer.from_pretrained("modelbert2/")
+tokenizer = AutoTokenizer.from_pretrained("peterkros/cofogv1-bert/modelbert2/")
 
 # Load the label encoder
 import pickle
-with open('label_encoder.pkl', 'rb') as file:
+with open('peterkros/cofogv1-bert/label_encoder.pkl', 'rb') as file:
     label_encoder = pickle.load(file)
 
 def predict(text):
@@ -31,9 +31,9 @@ def predict(text):
 
 # Define the markdown text with bullet points
 markdown_text = """
-- This is for test purpose only. 
+- Trainied with ~1500 rows of data on bert-base-uncased	110M, English
 - Input one budget line per time. 
-- Accuracy of the model is around 72%.
+- Accuracy of the model is ~72%.
 """
 
 # Define the interface