Update README.md

README.md

@@ -6,6 +6,7 @@ license: llama2
 We are glad to introduce our instruction finetuned code generation models based on CodeLLaMA: XwinCoder. We release model weights and evaluation code.
 
 **Repository:** [https://github.com/Xwin-LM/Xwin-LM/tree/main/Xwin-Coder](https://github.com/Xwin-LM/Xwin-LM/tree/main/Xwin-Coder)
+
 **Models:**
 | Model | 🤗hf link | HumanEval pass@1 | MBPP pass@1 | APPS-intro pass@5 |
 |-------|------------|----------|------|-------------|
@@ -14,9 +15,9 @@ We are glad to introduce our instruction finetuned code generation models based
 | XwinCoder-34B | [link](https://huggingface.co/Xwin-LM/XwinCoder-34B) | 74.2 | 64.8 | 43.0 |
 
 ## Updates
-- ❗We released  [**XwinCoder-7B**](https://huggingface.co/Xwin-LM/XwinCoder-7B), [**XwinCoder-13B**](https://huggingface.co/Xwin-LM/XwinCoder-13B), [**XwinCoder-34B**](https://huggingface.co/Xwin-LM/XwinCoder-34B). Our XwinCoder-34B reached 74.2 on HumanEval and it **achieves comparable performance as GPT-3.5-turbo on 6 benchmarks**.
+- 💥 We released  [**XwinCoder-7B**](https://huggingface.co/Xwin-LM/XwinCoder-7B), [**XwinCoder-13B**](https://huggingface.co/Xwin-LM/XwinCoder-13B), [**XwinCoder-34B**](https://huggingface.co/Xwin-LM/XwinCoder-34B). Our XwinCoder-34B reached 74.2 on HumanEval and it **achieves comparable performance as GPT-3.5-turbo on 6 benchmarks**.
 
-- ❗We support evaluating instruction finetuned models on HumanEval, MBPP, APPS, DS1000 and MT-Bench. We also conduct skywork-data-leakage experiments to check whether there are data leakage problems for open source models.
+- ❗We support evaluating instruction finetuned models on HumanEval, MBPP, APPS, DS1000 and MT-Bench. **We also conduct skywork-data-leakage experiments to check whether there are data leakage problems for open source models on huggingface.**
 
 ## Overview