Update README.md

README.md

@@ -3,7 +3,7 @@ library_name: peft
 datasets:
 - timdettmers/openassistant-guanaco
 pipeline_tag: conversational
-base_model: internlm/internlm2-7b
+base_model: internlm/internlm2-chat-7b
 ---
 
 <div align="center">
@@ -17,7 +17,7 @@ base_model: internlm/internlm2-7b
 
 ## Model
 
-internlm2-7b-qlora-oasst1 is fine-tuned from [InternLM2-7B](https://huggingface.co/internlm/internlm2-7b) with [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset by [XTuner](https://github.com/InternLM/xtuner).
+internlm2-chat-7b-qlora-oasst1 is fine-tuned from [InternLM2-Chat-7B](https://huggingface.co/internlm/internlm2-chat-7b) with [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset by [XTuner](https://github.com/InternLM/xtuner).
 
 
 ## Quickstart
@@ -33,7 +33,7 @@ pip install xtuner
 #### Chat
 
 ```shell
-xtuner chat internlm/internlm2-7b --adapter xtuner/internlm2-7b-qlora-oasst1 --prompt-template internlm2_chat
+xtuner chat internlm/internlm2-chat-7b --adapter xtuner/internlm2-chat-7b-qlora-oasst1 --prompt-template internlm2_chat
 ```
 
 #### Fine-tune
@@ -41,5 +41,5 @@ xtuner chat internlm/internlm2-7b --adapter xtuner/internlm2-7b-qlora-oasst1 --p
 Use the following command to quickly reproduce the fine-tuning results.
 
 ```shell
-xtuner train internlm2_7b_qlora_oasst1_e3
+xtuner train internlm2_chat_7b_qlora_oasst1_e3
 ```