Update README.md

README.md

@@ -13,7 +13,7 @@ tags:
 base_model:
 - beomi/KcELECTRA-base
 ---
-# Model Card for MisileLab/noMoreSpam
+# Model Card for MisileLab/noMoreSpamYT
 
 <!-- Provide a quick summary of what the model is/does. -->
 
@@ -25,7 +25,7 @@ A transformer-based model for detecting bot-generated spam comments on YouTube,
 
 <!-- Provide a longer summary of what this model is. -->
 
-noMoreSpam is a fine-tuned KcELECTRA model designed to identify and filter bot comments on YouTube videos. It specifically targets automated comments that promote adult content or gambling websites using repetitive patterns and specific keywords in Korean. The model uses a combination of CLS token and mean pooling strategies with custom classification layers to achieve high accuracy in distinguishing between human and bot-generated content.
+noMoreSpamYT is a fine-tuned KcELECTRA model designed to identify and filter bot comments on YouTube videos. It specifically targets automated comments that promote adult content or gambling websites using repetitive patterns and specific keywords in Korean. The model uses a combination of CLS token and mean pooling strategies with custom classification layers to achieve high accuracy in distinguishing between human and bot-generated content.
 
 - **Developed by:** MisileLab
 - **Model type:** Fine-tuned KcELECTRA for sequence classification
@@ -107,8 +107,8 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 
 # Load model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("MisileLab/noMoreSpam")
-model = AutoModelForSequenceClassification.from_pretrained("MisileLab/noMoreSpam")
+tokenizer = AutoTokenizer.from_pretrained("MisileLab/noMoreSpamYT")
+model = AutoModelForSequenceClassification.from_pretrained("MisileLab/noMoreSpamYT")
 
 # Prepare input
 comment = "여기 방문하세요 19금 즐거움이 가득합니다"  # Example spam comment