Update README.md

README.md

@@ -620,7 +620,7 @@ We also measure the inference speed and GPU memory usage with different settings
 ### Usage
 Now we provide the official training script, `finetune.py`, for users to finetune the pretrained model for downstream applications in a simple fashion. Additionally, we provide shell scripts to launch finetuning with no worries. This script supports the training with [DeepSpeed](https://github.com/microsoft/DeepSpeed) and [FSDP](https://engineering.fb.com/2021/07/15/open-source/fsdp/). The shell scripts that we provide use DeepSpeed (Note: this may have conflicts with the latest version of pydantic and you should use make sure `pydantic<2.0`) and Peft. You can install them by:
 ```bash
-pip install peft deepspeed
+pip install peft<0.8.0 deepspeed
 ```
 
 To prepare your training data, you need to put all the samples into a list and save it to a json file. Each sample is a dictionary consisting of an id and a list for conversation. Below is a simple example list with 1 sample: