Update model card

README.md

@@ -24,8 +24,8 @@ English gathered from social media platforms: Twitter and Gab. It achieved a **M
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 
 # Load model and tokenizer
-tokenizer = RobertaTokenizer.from_pretrained('tum-nlp/bertweet-sexism')
-model = RobertaForSequenceClassification.from_pretrained('tum-nlp/bertweet-sexism')
+tokenizer = AutoTokenizer.from_pretrained('tum-nlp/bertweet-sexism')
+model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/bertweet-sexism')
 
 # Create the pipeline for classification
 sexism_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)