Update app.py

app.py

@@ -5,11 +5,11 @@ from typing import Dict, List, Any
 import numpy as np
 
 # Load the model and tokenizer
-model = AutoModelForSequenceClassification.from_pretrained('kietnt0603/bertweet-base-hate-speech-offensive')
-tokenizer = AutoTokenizer.from_pretrained('kietnt0603/bertweet-base-hate-speech-offensive')
+model = AutoModelForSequenceClassification.from_pretrained('kietnt0603/visobert-vihds')
+tokenizer = AutoTokenizer.from_pretrained('kietnt0603/visobert-vihds')
 
 # Define the labels
-labels = ["Hate", "Offensive", "Neither"]
+labels = ["CLEAN", "OFFENSIVE", "HATE"]
 
 # Function for prediction
 def predict(inputs: str) -> Dict[str, Any]:
@@ -31,8 +31,8 @@ def predict(inputs: str) -> Dict[str, Any]:
 
 # Create title and description for the task
 title = "Text Classification Demo"
-description = "Classify text into categories: Hate, Offensive, Neither"
-article = "Model loaded from https://huggingface.co/kietnt0603/bertweet-base-hate-speech-offensive"
+description = "Classify text into categories: CLEAN, OFFENSIVE, HATE"
+article = "Model loaded from kietnt0603/visobert-vihds"
 
 # Create the Gradio interface
 iface = gr.Interface(fn=predict,