Update README.md

README.md

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 # **KoQuality-Polyglot-5.8b**
 
-KoQuality-Polyglot-5.8b is a fine-tuned iteration of the [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) model, specifically trained on the [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality). Notably, when excluding models employing COT datasets, KoQuality-Polyglot-5.8b exhibits exceptional performance, even though it operates with a relatively small dataset.
+KoQuality-Polyglot-5.8b is a fine-tuned iteration of the [EleutherAI/polyglot-ko-5.8b](https://huggingface.co/EleutherAI/polyglot-ko-5.8b) model, specifically trained on the [KoQuality dataset](https://huggingface.co/datasets/DILAB-HYU/KoQuality). Notably, when excluding models employing COT datasets, KoQuality-Polyglot-5.8b exhibits exceptional performance  in same size models, even though it operates with a relatively small dataset.
 
 ## Open Ko-LLM LeaderBoard
-<img src="https://cdn-uploads.huggingface.co/production/uploads/6152b4b9ecf3ca6ab820e325/iYzR_mdvkcjnVquho0Y9R.png"  width= "1000px">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/6152b4b9ecf3ca6ab820e325/iYzR_mdvkcjnVquho0Y9R.png"  width= "1000px"  title="하얀 강아지">
 
 Our approach centers around leveraging high-quality instruction datasets to deepen our understanding of commands, all the while preserving the performance of the Pre-trained Language Model (PLM). Compared to alternative models, we have achieved this with minimal learning, **utilizing only 1% of the dataset, which equates to 4006 instructions**.