fix

README.md

@@ -74,7 +74,7 @@ XTuner is an efficient, flexible and full-featured toolkit for fine-tuning large
 - Support various LLMs ([InternLM](https://huggingface.co/internlm), [Mixtral-8x7B](https://huggingface.co/mistralai), [Llama 2](https://huggingface.co/meta-llama), [ChatGLM](https://huggingface.co/THUDM), [Qwen](https://huggingface.co/Qwen), [Baichuan](https://huggingface.co/baichuan-inc), ...).
 - Support VLM ([LLaVA](https://github.com/haotian-liu/LLaVA)). The performance of [LLaVA-InternLM2-20B](https://huggingface.co/xtuner/llava-internlm2-20b) is outstanding.
 - Well-designed data pipeline, accommodating datasets in any format, including but not limited to open-source and custom formats.
-- Support various training algorithms ([QLoRA](http://arxiv.org/abs/2305.14314), [LoRA](http://arxiv.org/abs/2106.09685), full-parameter fune-tune), allowing users to choose the most suitable solution for their requirements.
+- Support various training algorithms ([QLoRA](http://arxiv.org/abs/2305.14314), [LoRA](http://arxiv.org/abs/2106.09685), full-parameter fine-tune), allowing users to choose the most suitable solution for their requirements.
 
 **Full-featured**
 
@@ -263,7 +263,7 @@ For more examples, please see [chat.md](./docs/en/user_guides/chat.md).
   pip install lmdeploy
   python -m lmdeploy.pytorch.chat ${NAME_OR_PATH_TO_LLM} \
       --max_new_tokens 256 \
-      --temperture 0.8 \
+      --temperature 0.8 \
       --top_p 0.95 \
       --seed 0
   ```