更新了Command-line-parameters.md里面的一个链接 (#1001)

Author: Shixian Sheng

docs/source/GetStarted/使用tuners.md

@@ -14,7 +14,7 @@ tuner是指附加在模型上的额外结构部分，用于减少训练参数量
 10. Adapter: [Parameter-Efficient Transfer Learning for NLP](http://arxiv.org/abs/1902.00751)
 11. Vision Prompt Tuning: [Visual Prompt Tuning](https://arxiv.org/abs/2203.12119)
 12. Side: [Side-Tuning: A Baseline for Network Adaptation via Additive Side Networks](https://arxiv.org/abs/1912.13503)
-13. Res-Tuning: [Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone](https://arxiv.org/abs/2310.19859)  < [arXiv](https://arxiv.org/abs/2310.19859)  |  [Project Page](https://res-tuning.github.io/)  |  [Usage](docs/source/GetStarted/ResTuning.md) >
+13. Res-Tuning: [Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone](https://arxiv.org/abs/2310.19859)  < [arXiv](https://arxiv.org/abs/2310.19859)  |  [Project Page](https://res-tuning.github.io/)  |  [Usage](ResTuning.md) >
 14. [PEFT](https://github.com/huggingface/peft)提供的tuners, 如IA3, AdaLoRA等
 
 ## 在训练中使用

docs/source_en/LLM/Command-line-parameters.md

@@ -312,7 +312,7 @@ The eval parameters inherit from the infer parameters, and additionally include
 
 - `--eval_few_shot`: The number of few-shot instances for each sub-dataset of the evaluation set, default is `None` which means using the default configuration of the dataset.
 
-- `--custom_eval_config`: Use a custom dataset for evaluation, this should be a local file path, the file format is described in [Custom Evaluation Set](./LLM-eval#Custom-Evaluation-Set).
+- `--custom_eval_config`: Use a custom dataset for evaluation, this should be a local file path, the file format is described in [Custom Evaluation Set](./LLM-eval.md#Custom-Evaluation-Set).
 
 - `--eval_use_cache`: Whether to use the evaluation cache, if True, the eval process will only refresh the eval results. Default `False`.