Update README.md

README.md

@@ -12,7 +12,7 @@ pinned: false
 
 <div id="top" align="center">
 
-**Knowledge Fusion of Large Language Models**
+<p style="font-size: 44px; font-weight: bold;">Knowledge Fusion of Large Language Models</p>
 
 
 <h4> |<a href="https://arxiv.org/abs/2401.10491"> 📑 FuseLLM Paper @ICLR2024 </a> |
@@ -22,7 +22,7 @@ pinned: false
 </h4>
 
 <p align="center">
-    <img src="https://github.com/18907305772/FuseLLM/blob/main/assets/logo.png" width="95%"> <br>
+    <img src="logo.png" width="60%"> <br>
 </p>
 
 </div>
@@ -35,7 +35,7 @@ pinned: false
 - **Feb 26, 2024:** 🔥🔥 We release [FuseChat-7B-VaRM](https://huggingface.co/FuseAI/FuseChat-7B-VaRM), which is the fusion of three prominent chat LLMs with diverse architectures and scales, namely [NH2-Mixtral-8x7B](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO), [NH2-Solar-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B), and [OpenChat-3.5-7B](https://huggingface.co/openchat/openchat_3.5). FuseChat-7B-VaRM achieves an average performance of **8.22** on MT-Bench, outperforming various powerful chat LLMs like [Starling-7B](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha), [Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat), and [Tulu-2-DPO-70B](https://huggingface.co/allenai/tulu-2-dpo-70b), even surpassing [GPT-3.5 (March)](https://platform.openai.com/docs/models/gpt-3-5-turbo), [Claude-2.1](https://www.anthropic.com/news/claude-2-1), and approaching [Mixtral-8x7B-Instruct](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1).
 
 <p align="center">
-    <img src="https://github.com/18907305772/FuseLLM/blob/main/FuseChat/assets/fig_0.png" width="70%"> <br>
+    <img src="fig_0.png" width="40%"> <br>
 </p>
 
 | Priority Models                                                       | #Params | MT-Bench | Open Source Models                                                    | #Params | MT-Bench |