Update README.md

README.md

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-## CREST: CRoss-lingual Efficient Safety Transfer  
+## CREST: Universal Safety Guardrails Through Cluster-Guided Cross-Lingual Transfer  
 **A Multilingual Safety Guardrail Model for 100 languages built on XLM-RoBERTa**
 
-CREST is a parameter-efficient multilingual safety classifier for 100 languages, fine-tuned using 13 strategically selected high-resource languages only, chosen through cluster-guided sampling, enabling strong cross-lingual transfer to unseen low-resource languages. 
+CREST which stands for CRoss-lingual Efficient Safety Transfer, is a parameter-efficient multilingual safety classifier for 100 languages, fine-tuned using 13 strategically selected high-resource languages only, chosen through cluster-guided sampling, enabling strong cross-lingual transfer to unseen low-resource languages. 
 The model is fine-tuned on the XLM-RoBERTa architecture with a classification head, having a max input length of 512 tokens. The CREST model comes in two variants: 
 - `CREST-Base` approximately 278M parameters  
 - `CREST-Large` approximately 560M parameters