Support qwen2 (#1093)

Author: Jintao-Huang

README.md

@@ -47,7 +47,7 @@ SWIFT has rich documentations for users, please check [here](https://github.com/
 SWIFT web-ui is available both on [Huggingface space](https://huggingface.co/spaces/tastelikefeet/swift) and [ModelScope studio](https://www.modelscope.cn/studios/iic/Scalable-lightWeight-Infrastructure-for-Fine-Tuning/summary), please feel free to try!
 
 ## 🎉 News
-- 🔥2024.06.07: Support Qwen2 series LLM, including Base and Instruct models of 0.5B, 1.5B, 7B, and 72B, as well as corresponding quantized versions gptq-int4, gptq-int8, and awq-int4.
+- 🔥2024.06.07: Support **Qwen2** series LLM, including Base and Instruct models of 0.5B, 1.5B, 7B, and 72B, as well as corresponding quantized versions gptq-int4, gptq-int8, and awq-int4. The best practice for self-cognition fine-tuning, inference and deployment of Qwen2-72B-Instruct using dual-card 80GiB A100 can be found [here](https://github.com/modelscope/swift/issues/1092).
 - 🔥2024.06.05: Support for **glm4** series LLM and glm4v-9b-chat MLLM. You can refer to [glm4v best practice](docs/source_en/Multi-Modal/glm4v-best-practice.md).
 - 🔥2024.06.01: Supoprts **SimPO** training! See [document](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/SimPO.md) to start training!
 - 🔥2024.06.01: Support for deploying large multimodal models, please refer to the [Multimodal Deployment Documentation](docs/source_en/Multi-Modal/mutlimodal-deployment.md) for more information.

README_CN.md

@@ -48,7 +48,7 @@ SWIFT具有丰富的文档体系，如有使用问题请请查看[这里](https:
 可以在[Huggingface space](https://huggingface.co/spaces/tastelikefeet/swift) 和 [ModelScope创空间](https://www.modelscope.cn/studios/iic/Scalable-lightWeight-Infrastructure-for-Fine-Tuning/summary) 中体验SWIFT web-ui功能了。
 
 ## 🎉 新闻
-- 🔥2024.06.07: 支持Qwen2系列LLM, 包括0.5B、1.5B、7B、72B的Base和Instruct模型, 以及对应的gptq-int4、gptq-int8、awq-int4量化版本.
+- 🔥2024.06.07: 支持**Qwen2**系列LLM, 包括0.5B、1.5B、7B、72B的Base和Instruct模型, 以及对应的gptq-int4、gptq-int8、awq-int4量化版本. 使用双卡80GiB A100对Qwen2-72B-Instruct进行自我认知微调并推理部署的最佳实践可以查看[这里](https://github.com/modelscope/swift/issues/1092).
 - 🔥2024.06.05: 支持glm4系列大模型和glm4v-9b-chat多模态大模型, 可以查看[glm4v最佳实践](docs/source/Multi-Modal/glm4v最佳实践.md).
 - 🔥2024.06.01: 支持**SimPO**训练，使用`swift simpo`来开始训练，最佳实践可以查看[这里](https://github.com/modelscope/swift/tree/main/docs/source/LLM/SimPO算法最佳实践.md)
 - 🔥2024.06.01: 支持多模态大模型部署, 可以查看[多模态部署文档](docs/source/Multi-Modal/MLLM部署文档.md).

docs/source/LLM/Qwen1.5全流程最佳实践.md

@@ -3,6 +3,8 @@
 
 这里介绍对**Qwen1.5-7B-Chat**和对**Qwen1.5-72B-Chat**进行推理, 自我认知微调, 量化, 部署. 分别对应**低配置和高配置**环境.
 
+使用双卡80GiB A100对**Qwen2-72B-Instruct**进行自我认知微调并推理部署的最佳实践可以查看[这里](https://github.com/modelscope/swift/issues/1092).
+
 
 ## 目录
 - [环境准备](#环境准备)

docs/source_en/LLM/Qwen1.5-best-practice.md

@@ -2,6 +2,9 @@
 
 This introduces how to perform inference, self-cognition fine-tuning, quantization, and deployment on **Qwen1.5-7B-Chat** and **Qwen1.5-72B-Chat**, corresponding to **low-resource and high-resource** environments respectively.
 
+The best practice for self-cognition fine-tuning, inference and deployment of Qwen2-72B-Instruct using dual-card 80GiB A100 can be found [here](https://github.com/modelscope/swift/issues/1092).
+
+
 ## Table of Contents
 - [Environment Preparation](#environment-preparation)
 - [Qwen1.5-7B-Chat](#qwen15-7b-chat)

tests/llm/test_run2.py

@@ -18,7 +18,7 @@
 logger = get_logger()
 
 
-class TestRun(unittest.TestCase):
+class TestRun2(unittest.TestCase):
 
     def setUp(self):
         print(f'Testing {type(self).__name__}.{self._testMethodName}')