changed to BERTic

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from sentiwordnet_calculator import SentimentPipeline
 
-pipe = SentimentPipeline("Tanor/SRGPTSENTPOS2", "Tanor/SRGPTSENTNEG2")
+pipe = SentimentPipeline("Tanor/BERTicSENTPOS4", "Tanor/BERTicSENTNEG4")
 
 def calculate(text):
     result = pipe(text)
@@ -20,8 +20,8 @@ iface = gr.Interface(
     title="Sentiment Analysis for Serbian",
     description="""
     This tool performs sentiment analysis on the input text using a model trained on Serbian dictionary definitions. 
-    The model was initially pretrained on the [sr-gpt2-large model by Mihailo Škorić](https://huggingface.co/JeRTeh/sr-gpt2-large), 
-    then fine-tuned on selected definitions from the Serbian WordNet. Please limit the input to 300 tokens. 
+    The pretrained model [BERTic from classla](https://huggingface.co/classla/bcms-bertic), 
+    was fine-tuned on selected definitions from the Serbian WordNet. Please limit the input to 300 tokens. 
     The outputs represent the Positive (POS), Negative (NEG), and Objective (OBJ) sentiment scores.
     """,
     examples=[