Update README.md

README.md

@@ -9,7 +9,7 @@ pipeline_tag: text-generation
 
 # SLIMER: Show Less Instruct More Entity Recognition
 
-SLIMER is an instruction-tuned LLaMA-2-7B model for zero-shot NER.
+SLIMER is an instruction-tuned LLM for zero-shot NER.
 
 Instructed on a reduced number of samples, it is designed to tackle never-seen-before Named Entity tags by leveraging a prompt enriched with a DEFINITION and GUIDELINES for the NE to be extracted.
 
@@ -20,3 +20,5 @@ SLIMER performs comparably to these state-of-the-art approaches on OOD input dom
 
 <img src="https://huggingface.co/expertai/SLIMER/resolve/main/OOD_evals.png">
 
+To experiment the ability of existing models on never-seen-before labels, we extend the standard zero-shot evaluations on BUSTER, which is characterized by financial entities that are rather far from the more traditional tags observed by all models during training.
+An inverse trend to the OOD table can be observed, with SLIMER instead emerging as the most effective in dealing with unseen labels, thanks to its lighter instruction tuning methodology and the use of definition and guidelines.