Update app.py

app.py

@@ -3,12 +3,10 @@ import torch.nn as nn
 from transformers import BertTokenizer, BertModel
 import gradio as gr
 
-# Load tokenizer and base BERT model
-model_name = "keerthikapujari25/bert-emotion-classifier"  # Replace with your HF username/repo
+model_name = "keethu/bert-emotion-classifier"  
 tokenizer = BertTokenizer.from_pretrained(model_name)
 bert_model = BertModel.from_pretrained(model_name)
 
-# Define your classifier architecture (same as training)
 class BERTClassifier(nn.Module):
     def __init__(self, bert_model, num_labels=5, dropout=0.3):
         super(BERTClassifier, self).__init__()
@@ -23,7 +21,6 @@ class BERTClassifier(nn.Module):
         logits = self.classifier(pooled_output)
         return logits
 
-# Load model
 model = BERTClassifier(bert_model, num_labels=5, dropout=0.3)
 model.load_state_dict(torch.load(f"{model_name}/pytorch_model.bin", map_location='cpu'))
 model.eval()