Update README.md

README.md

@@ -45,10 +45,13 @@ configs:
 ### **UniIR: Training and Benchmarking Universal Multimodal Information Retrievers**
 [**🌐 Homepage**](https://tiger-ai-lab.github.io/UniIR/) | [**🤗 Paper**](https://huggingface.co/papers/2311.17136) | [**📖 arXiv**](https://arxiv.org/pdf/2311.17136.pdf)  | [**GitHub**](https://github.com/TIGER-AI-Lab/UniIR)
 
+## 🔔News
+
+- **🔥[2023-12-21]: Our M-BEIR Benchmark is now available for use.**
 
 ## **Dataset Summary**
 
-M-BEIR, the **M**ultimodal **BE**nchmark for **I**nstructed **R**etrieval, is a comprehensive large-scale retrieval benchmark designed to train and evaluate unified multimodal retrieval models (**UniIR models**).
+**M-BEIR**, the **M**ultimodal **BE**nchmark for **I**nstructed **R**etrieval, is a comprehensive large-scale retrieval benchmark designed to train and evaluate unified multimodal retrieval models (**UniIR models**).
 The M-BEIR benchmark comprises eight multimodal retrieval tasks and ten datasets from a variety of domains and sources. 
 Each task is accompanied by human-authored instructions, encompassing 1.5 million queries and a pool of 5.6 million retrieval candidates in total.
 
@@ -145,10 +148,10 @@ The structure of each candidate JSON object in cand_pool file is as follows::
 ```
 
 ### Instructions
-`query_instructions.tsv` contains human-authorized instructions within the UniIR framework. Each task is accompanied by four human-authored instructions.
+`query_instructions.tsv` contains human-authorized instructions within the UniIR framework. Each task is accompanied by four human-authored instructions. For detailed usage, please refer to [**GitHub Repo**](https://github.com/TIGER-AI-Lab/UniIR).
 
 ### Qrels
-Within the `qrels` directory, you will find qrels for both the validation and test sets. These files serve the purpose of evaluating UniIR models.
+Within the `qrels` directory, you will find qrels for both the validation and test sets. These files serve the purpose of evaluating UniIR models.  For detailed information, please refer to [**GitHub Repo**](https://github.com/TIGER-AI-Lab/UniIR).
 
 ## **How to Use**
 ### Downloading the M-BEIR Dataset