Update README.md

README.md

@@ -174,7 +174,7 @@ The intermediate stage checkpoints are released in <a href="https://huggingface.
 
 <details><summary>3. Optimizer States Before Annealing</summary>
 
-Optimizer states before annealing will be released in a future update.
+<a href="https://huggingface.co/yulan-team/YuLan-Mini-Before-Annealing">YuLan-Mini-Before-Annealing</a>
 </details>
 
 
@@ -213,11 +213,11 @@ Intermediate optimizer states will be released in a future update.
 
 ### What you can do with these pre-training resources
 
-1. **Pre-train** your own LLM. You can use our data and curriculum to train a model that's just as powerful as YuLan-Mini.
-2. Perform your own **learning rate annealing**. During the annealing phase, YuLan-Mini's learning ability is at its peak. You can resume training from the checkpoint before annealing and use your own dataset for learning rate annealing.
+1. **Pre-train** your own LLM. You can use [our data](https://huggingface.co/yulan-team/YuLan-Mini-Datasets) and curriculum to train a model that's just as powerful as YuLan-Mini.
+2. Perform your own **learning rate annealing**. During the annealing phase, YuLan-Mini's learning ability is at its peak. You can resume training from [the checkpoint before annealing](https://huggingface.co/yulan-team/YuLan-Mini-Before-Annealing) and use your own dataset for learning rate annealing.
 3. **Fine-tune** the Instruct version of the LLM. You can use the YuLan-Mini base model to train your own Instruct version.
 4. **Training dynamics** research. You can use YuLan-Mini's intermediate checkpoints to explore internal changes during the pre-training process.
-5. **Synthesize** your own data. You can use YuLan-Mini's data pipeline to clean and generate your own dataset.
+5. **Synthesize** your own data. You can use YuLan-Mini's [data pipeline](https://github.com/RUC-GSAI/YuLan-Mini) to clean and generate your own dataset.
 
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@@ -255,6 +255,10 @@ python -m sglang.launch_server --model-path yulan-team/YuLan-Mini --port 30000 -
 
 ---
 
+## The Team
+
+YuLan-Mini is developed and maintained by [AI Box, Renmin University of China](http://aibox.ruc.edu.cn/).
+
 ## License
 
 - The code in this repository is released under the [MIT License](./LICENSE).