update readme (#291)

Author: Jintao-Huang

README.md

@@ -111,7 +111,8 @@ Users can check the [documentation of SWIFT](docs/source/GetStarted/快速使用
 ### Simple Usage
 - **Self-cognitionfine-tuning** for large models in **10 minutes**, creating a personalized large model, please refer to [Best Practices for Self-cognition Fine-tuning](https://github.com/modelscope/swift/blob/main/docs/source/LLM/自我认知微调最佳实践.md).
 - Quickly perform **inference** on LLM and build a **Web-UI**, see the [LLM Inference Documentation](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM推理文档.md).
-- Rapidly **fine-tune** and perform inference on LLM, and build a Web-UI. See the [LLM Fine-tuning Documentation](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM微调文档.md) and [WEB-UI Documentation](https://github.com/modelscope/swift/blob/main/docs/source/GetStarted/%E7%95%8C%E9%9D%A2%E8%AE%AD%E7%BB%83%E6%8E%A8%E7%90%86.md).
+- Rapidly **fine-tune** and perform inference on LLM, and build a Web-UI, see the [LLM Fine-tuning Documentation](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM微调文档.md).
+- Using **interface** to fine-tuning and perform inference, see the [WEB-UI Documentation](https://github.com/modelscope/swift/blob/main/docs/source/GetStarted/%E7%95%8C%E9%9D%A2%E8%AE%AD%E7%BB%83%E6%8E%A8%E7%90%86.md).
 - **DPO training** supported, start by using [this script](https://github.com/modelscope/swift/blob/v1.5.0/examples/pytorch/llm/scripts/dpo/lora/dpo.sh).
 - Utilize VLLM for **inference acceleration** and **deployment(OpenAI API)**. Please refer to [VLLM Inference Acceleration and Deployment](https://github.com/modelscope/swift/blob/main/docs/source/LLM/VLLM推理加速与部署.md) for more information.
 - View the models and datasets supported by Swift. You can check [supported models and datasets](https://github.com/modelscope/swift/blob/main/docs/source/LLM/支持的模型和数据集.md).
@@ -121,7 +122,7 @@ Users can check the [documentation of SWIFT](docs/source/GetStarted/快速使用
 
 
 ### Features
-- Supported SFT Methods: [lora](https://arxiv.org/abs/2106.09685), [qlora](https://arxiv.org/abs/2305.14314), full(full parameter fine-tuning)
+- Supported SFT Methods: [lora](https://arxiv.org/abs/2106.09685), [qlora](https://arxiv.org/abs/2305.14314), longlora, qalora, full(full parameter fine-tuning), partial parameter fine-tuning.
 - Supported Features: quantization, DDP, model parallelism, gradient checkpointing, pushing to modelscope hub, custom datasets, multimodal and agent SFT, mutli-round chat, ...
 - Supported Models: [[Detail]](https://github.com/modelscope/swift/blob/main/docs/source/LLM/%E6%94%AF%E6%8C%81%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86.md#%E6%A8%A1%E5%9E%8B)
   - Multi-Modal:

README_CN.md

@@ -109,7 +109,8 @@ SWIFT（Scalable lightWeight Infrastructure for Fine-Tuning）是一个可扩展
 ### 简单使用
 - **10分钟**对大模型进行**自我认知微调**, 创建专属于自己的大模型, 可以查看[自我认知微调最佳实践](https://github.com/modelscope/swift/blob/main/docs/source/LLM/自我认知微调最佳实践.md).
 - 快速对LLM进行**推理**, 搭建**Web-UI**, 可以查看[LLM推理文档](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM推理文档.md).
-- 快速对LLM进行**微调**, 推理并搭建Web-UI. 可以查看[LLM微调文档](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM微调文档.md) 和 [WEB-UI文档](https://github.com/modelscope/swift/blob/main/docs/source/GetStarted/%E7%95%8C%E9%9D%A2%E8%AE%AD%E7%BB%83%E6%8E%A8%E7%90%86.md).
+- 快速对LLM进行**微调**, 推理并搭建Web-UI, 可以查看[LLM微调文档](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM微调文档.md).
+- 使用**界面**方式进行微调和推理, 可以查看[WEB-UI文档](https://github.com/modelscope/swift/blob/main/docs/source/GetStarted/%E7%95%8C%E9%9D%A2%E8%AE%AD%E7%BB%83%E6%8E%A8%E7%90%86.md).
 - 支持**DPO训练**, 使用[这个脚本](https://github.com/modelscope/swift/blob/v1.5.0/examples/pytorch/llm/scripts/dpo/lora/dpo.sh)开启训练
 - 使用VLLM进行**推理加速**和**部署(OpenAI API)**. 可以查看[VLLM推理加速与部署](https://github.com/modelscope/swift/blob/main/docs/source/LLM/VLLM推理加速与部署.md).
 - 查看swift支持的模型和数据集. 可以查看[支持的模型和数据集](https://github.com/modelscope/swift/blob/main/docs/source/LLM/支持的模型和数据集.md).
@@ -119,7 +120,7 @@ SWIFT（Scalable lightWeight Infrastructure for Fine-Tuning）是一个可扩展
 
 
 ### 特性
-- 支持的SFT方法: [lora](https://arxiv.org/abs/2106.09685), [qlora](https://arxiv.org/abs/2305.14314), 全参数微调
+- 支持的SFT方法: [lora](https://arxiv.org/abs/2106.09685), [qlora](https://arxiv.org/abs/2305.14314), longlora, qalora, 全参数微调, 部分参数微调.
 - 支持的特性: 模型量化, DDP, 模型并行, gradient checkpointing, 支持推送ModelScope Hub, 自定义数据集, 多模态和Agent SFT, 多轮对话, ...
 - 支持的模型: [[详细]](https://github.com/modelscope/swift/blob/main/docs/source/LLM/%E6%94%AF%E6%8C%81%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86.md#%E6%A8%A1%E5%9E%8B)
   - 多模态:

swift/llm/utils/utils.py

@@ -278,7 +278,7 @@ def dataset_map(dataset: HfDataset,
         data = _map_mp(dataset, single_map, num_proc)
     data = [d for d in data if d is not None]
     if len(data) == 0:
-        logger.info('len(dataset): 0')
+        logger.warning('len(dataset): 0')
         return None
     return LLMDataset(data)