Update README.md

README.md

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   <a href="#model">Model</a> •
   <a href="#data">Data Release</a> •
   <a href="#web-ui">Web Demo</a> •
-  <a href="#tool-eval">Tool Eval</a> •
+  <a href="#tooleval">Tool Eval</a> •
   <a href="https://arxiv.org/pdf/2307.16789.pdf">Paper</a> •
   <a href="#citation">Citation</a>
 
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 </div>
 
 <div align="center">
-<img src="https://cdn.discordapp.com/attachments/941582479117127680/1111543600879259749/20230526075532.png" width="350px">
+<img src="assets/ToolLLaMA-logo.png" width="350px">
 </div>
 
 🔨This project (ToolLLM) aims to construct **open-source, large-scale, high-quality** instruction tuning SFT data to facilitate the construction of powerful LLMs with general **tool-use** capability. We aim to empower open-source LLMs to master thousands of diverse real-world APIs. We achieve this by collecting a high-quality instruction-tuning dataset. It is constructed automatically using the latest ChatGPT (gpt-3.5-turbo-16k), which is upgraded with enhanced [function call](https://openai.com/blog/function-calling-and-other-api-updates) capabilities. We provide the dataset, the corresponding training and evaluation scripts, and a capable model ToolLLaMA fine-tuned on ToolBench.