diff --git a/README.md b/README.md index 974b30d0..9a4bd934 100644 --- a/README.md +++ b/README.md @@ -174,9 +174,9 @@ Compared to ChatGLM's [P-Tuning](https://github.com/THUDM/ChatGLM2-6B/tree/main/ | [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | q_proj,v_proj | yuan | > [!NOTE] -> **Default module** is used for the `--lora_target` argument, you can use `--lora_target all` to specify all the available modules for better convergence. +> **Default module** is used for the `lora_target` argument, you can use `lora_target: all` to specify all the available modules for better convergence. > -> For the "base" models, the `--template` argument can be chosen from `default`, `alpaca`, `vicuna` etc. But make sure to use the **corresponding template** for the "instruct/chat" models. +> For the "base" models, the `template` argument can be chosen from `default`, `alpaca`, `vicuna` etc. But make sure to use the **corresponding template** for the "instruct/chat" models. > > Remember to use the **SAME** template in training and inference. @@ -448,7 +448,16 @@ If you have trouble with downloading models and datasets from Hugging Face, you export USE_MODELSCOPE_HUB=1 # `set USE_MODELSCOPE_HUB=1` for Windows ``` -Train the model by specifying a model ID of the ModelScope Hub as the `--model_name_or_path`. You can find a full list of model IDs at [ModelScope Hub](https://modelscope.cn/models), e.g., `LLM-Research/Meta-Llama-3-8B-Instruct`. +Train the model by specifying a model ID of the ModelScope Hub as the `model_name_or_path`. You can find a full list of model IDs at [ModelScope Hub](https://modelscope.cn/models), e.g., `LLM-Research/Meta-Llama-3-8B-Instruct`. + +### Use W&B Logging + +To use [Weights & Biases](https://wandb.ai) for logging experimental results, you need to add the following arguments. + +```yaml +report_to: wandb +run_name: test_run # optional +``` ## Projects using LLaMA Factory diff --git a/README_zh.md b/README_zh.md index 7106bbab..73426a7f 100644 --- a/README_zh.md +++ b/README_zh.md @@ -174,9 +174,9 @@ https://github.com/hiyouga/LLaMA-Factory/assets/16256802/ec36a9dd-37f4-4f72-81bd | [Yuan](https://huggingface.co/IEITYuan) | 2B/51B/102B | q_proj,v_proj | yuan | > [!NOTE] -> **默认模块**应作为 `--lora_target` 参数的默认值,可使用 `--lora_target all` 参数指定全部模块以取得更好的效果。 +> **默认模块**应作为 `lora_target` 参数的默认值,可使用 `lora_target: all` 参数指定全部模块以取得更好的效果。 > -> 对于所有“基座”(Base)模型,`--template` 参数可以是 `default`, `alpaca`, `vicuna` 等任意值。但“对话”(Instruct/Chat)模型请务必使用**对应的模板**。 +> 对于所有“基座”(Base)模型,`template` 参数可以是 `default`, `alpaca`, `vicuna` 等任意值。但“对话”(Instruct/Chat)模型请务必使用**对应的模板**。 > > 请务必在训练和推理时使用**完全一致**的模板。 @@ -446,7 +446,16 @@ CUDA_VISIBLE_DEVICES=0,1 API_PORT=8000 llamafactory-cli api examples/inference/l export USE_MODELSCOPE_HUB=1 # Windows 使用 `set USE_MODELSCOPE_HUB=1` ``` -将 `--model_name_or_path` 设置为模型 ID 来加载对应的模型。在[魔搭社区](https://modelscope.cn/models)查看所有可用的模型,例如 `LLM-Research/Meta-Llama-3-8B-Instruct`。 +将 `model_name_or_path` 设置为模型 ID 来加载对应的模型。在[魔搭社区](https://modelscope.cn/models)查看所有可用的模型,例如 `LLM-Research/Meta-Llama-3-8B-Instruct`。 + +### 使用 W&B 面板 + +若要使用 [Weights & Biases](https://wandb.ai) 记录实验数据,请添加下面的参数。 + +```yaml +report_to: wandb +run_name: test_run # 可选 +``` ## 使用了 LLaMA Factory 的项目