modelscope · Jintao-Huang · Jun 28, 2024 · Jun 28, 2024 · Jun 28, 2024 · Jun 28, 2024
diff --git a/README.md b/README.md
@@ -47,6 +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
+- 🔥2024.06.28: Support for Gemma2 series models: gemma2-9b, gemma2-9b-instruct, gemma2-27b, gemma2-27b-instruct.
 - 🔥2024.06.18: Supports **DeepSeek-Coder-v2** series model! Use model_type `deepseek-coder-v2-instruct` and `deepseek-coder-v2-lite-instruct` to begin.
 - 🔥2024.06.16: Supports **KTO** and **CPO** training! See [document](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/Human-Preference-Alignment-Training-Documentation.md) to start training!
 - 2024.06.11: Support for tool-calling agent deployment that conform to the OpenAI interface.You can refer to [Agent deployment best practice](https://github.com/modelscope/swift/blob/main/docs/source_en/LLM/Agent-deployment-best-practice.md)
@@ -512,7 +513,7 @@ The complete list of supported models and datasets can be found at [Supported Mo
 | InternLM<br>InternLM2<br>InternLM2-Math              | [Pujiang AI Lab InternLM series models](https://github.com/InternLM/InternLM) | Chinese<br>English | 1.8B-20B                            | base model<br>chat model<br>math model            |
 | DeepSeek<br>DeepSeek-MoE<br>DeepSeek-Coder<br>DeepSeek-Math<br>DeepSeek-V2<br>DeepSeek-Coder-V2          | [DeepSeek series models](https://github.com/deepseek-ai)       | Chinese<br>English    | 1.3B-236B                               | base model<br>chat model<br>MoE model<br>code model<br>math model |
 | MAMBA                                          | [MAMBA temporal convolution model](https://github.com/state-spaces/mamba) | English          | 130M-2.8B                              | base model                                 |
-| Gemma                                          | [Google Gemma series models](https://github.com/google/gemma_pytorch)   | English            | 2B-7B                                  | base model<br>instruct model                       |
+| Gemma<br>Gemma2                                     | [Google Gemma series models](https://github.com/google/gemma_pytorch)   | English            | 2B-27B                                  | base model<br>instruct model                       |
 | MiniCPM                                        | [OpenBmB MiniCPM series models](https://github.com/OpenBMB/MiniCPM)     | Chinese<br>English    | 2B-3B                                  | chat model<br>MoE model                                 |
 | OpenBuddy                                      | [OpenBuddy series models](https://github.com/OpenBuddy/OpenBuddy)       | Chinese<br>English    | 7B-70B                                 | base model<br>chat model                       |
 | Orion                                          | [OrionStar AI series models](https://github.com/OrionStarAI)            | Chinese<br>English    | 14B                                    | base model<br>chat model                       |

diff --git a/README_CN.md b/README_CN.md
@@ -48,6 +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
+- 🔥2024.06.28: 支持**Gemma2**系列模型: gemma2-9b, gemma2-9b-instruct, gemma2-27b, gemma2-27b-instruct.
 - 🔥2024.06.18: 支持**DeepSeek-Coder-v2**系列模型! 使用model_type`deepseek-coder-v2-instruct`和`deepseek-coder-v2-lite-instruct`来开启训练和推理.
 - 🔥2024.06.16: 支持**KTO**和**CPO**训练，使用`swift rlhf --rlhf_type kto`和`swift rlhf --rlhf_type cpo`来开始训练，可以参考[文档](./docs/source/LLM/人类偏好对齐训练文档.md).
 - 2024.06.11: 支持符合OpenAI接口的工具调用Agent部署, 可以查看[Agent部署最佳实践](docs/source/LLM/Agent部署最佳实践.md).
@@ -508,7 +509,7 @@ CUDA_VISIBLE_DEVICES=0 swift deploy \
 | InternLM<br>InternLM2<br>InternLM2-Math                   | [浦江实验室书生浦语系列模型](https://github.com/InternLM/InternLM) | 中文<br>英文 | 1.8B-20B                  | base模型<br>chat模型<br>数学模型                  |
 | DeepSeek<br>DeepSeek-MoE<br>DeepSeek-Coder<br>DeepSeek-Math<br>DeepSeek-V2<br>DeepSeek-Coder-V2       | [幻方系列模型](https://github.com/deepseek-ai)               | 中文<br>英文 | 1.3B-236B                  | base模型<br>chat模型<br>MoE模型<br>代码模型<br>数学模型 |
 | MAMBA                                               | [MAMBA时序卷积模型](https://github.com/state-spaces/mamba)   | 英文       | 130M-2.8B                 | base模型                                    |
-| Gemma                                               | [Google Gemma系列模型](https://github.com/google/gemma_pytorch) | 英文       | 2B-7B                     | base模型<br>instruct模型                      |
+| Gemma<br>Gemma2                                       | [Google Gemma系列模型](https://github.com/google/gemma_pytorch) | 英文       | 2B-27B                     | base模型<br>instruct模型                      |
 | MiniCPM                                             | [OpenBmB MiniCPM系列模型](https://github.com/OpenBMB/MiniCPM) | 中文<br>英文 | 2B-3B                     | chat模型<br>MoE模型                                    |
 | OpenBuddy                                           | [OpenBuddy系列模型](https://github.com/OpenBuddy/OpenBuddy)  | 中文<br>英文 | 7B-70B                    | base模型<br>chat模型                          |
 | Orion                                               | [猎户星空系列模型](https://github.com/OrionStarAI)           | 中文<br>英文 | 14B                       | base模型<br>chat模型                          |

diff --git a/docs/source/LLM/支持的模型和数据集.md b/docs/source/LLM/支持的模型和数据集.md
@@ -216,6 +216,10 @@
 |gemma-7b|[AI-ModelScope/gemma-7b](https://modelscope.cn/models/AI-ModelScope/gemma-7b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-7b](https://huggingface.co/google/gemma-7b)|
 |gemma-2b-instruct|[AI-ModelScope/gemma-2b-it](https://modelscope.cn/models/AI-ModelScope/gemma-2b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it)|
 |gemma-7b-instruct|[AI-ModelScope/gemma-7b-it](https://modelscope.cn/models/AI-ModelScope/gemma-7b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it)|
+|gemma2-9b|[LLM-Research/gemma-2-9b](https://modelscope.cn/models/LLM-Research/gemma-2-9b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b)|
+|gemma2-27b|[LLM-Research/gemma-2-27b](https://modelscope.cn/models/LLM-Research/gemma-2-27b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b)|
+|gemma2-9b-instruct|[LLM-Research/gemma-2-9b-it](https://modelscope.cn/models/LLM-Research/gemma-2-9b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)|
+|gemma2-27b-instruct|[LLM-Research/gemma-2-27b-it](https://modelscope.cn/models/LLM-Research/gemma-2-27b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it)|
 |minicpm-1b-sft-chat|[OpenBMB/MiniCPM-1B-sft-bf16](https://modelscope.cn/models/OpenBMB/MiniCPM-1B-sft-bf16/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;|transformers>=4.36.0|-|[openbmb/MiniCPM-1B-sft-bf16](https://huggingface.co/openbmb/MiniCPM-1B-sft-bf16)|
 |minicpm-2b-sft-chat|[OpenBMB/MiniCPM-2B-sft-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-sft-fp32/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;||-|[openbmb/MiniCPM-2B-sft-fp32](https://huggingface.co/openbmb/MiniCPM-2B-sft-fp32)|
 |minicpm-2b-chat|[OpenBMB/MiniCPM-2B-dpo-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-dpo-fp32/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;||-|[openbmb/MiniCPM-2B-dpo-fp32](https://huggingface.co/openbmb/MiniCPM-2B-dpo-fp32)|
@@ -416,6 +420,7 @@
 |webnovel-zh|[AI-ModelScope/webnovel_cn](https://modelscope.cn/datasets/AI-ModelScope/webnovel_cn/summary)||50000|1478.9±11526.1, min=100, max=490484|chat, novel|[zxbsmk/webnovel_cn](https://huggingface.co/datasets/zxbsmk/webnovel_cn)|
 |generated-chat-zh|[AI-ModelScope/generated_chat_0.4M](https://modelscope.cn/datasets/AI-ModelScope/generated_chat_0.4M/summary)||396004|273.3±52.0, min=32, max=873|chat, character-dialogue|[BelleGroup/generated_chat_0.4M](https://huggingface.co/datasets/BelleGroup/generated_chat_0.4M)|
 |🔥self-cognition|[swift/self-cognition](https://modelscope.cn/datasets/swift/self-cognition/summary)||134|53.6±18.6, min=29, max=121|chat, self-cognition|[modelscope/self-cognition](https://huggingface.co/datasets/modelscope/self-cognition)|
+|🔥swift-mix|[swift/swift-sft-mixture](https://modelscope.cn/datasets/swift/swift-sft-mixture/summary)|sharegpt<br>firefly<br>codefuse<br>metamathqa|-|Dataset is too huge, please click the original link to view the dataset stat.|chat, sft, general|-|
 |cls-fudan-news-zh|[damo/zh_cls_fudan-news](https://modelscope.cn/datasets/damo/zh_cls_fudan-news/summary)||4959|3234.4±2547.5, min=91, max=19548|chat, classification|-|
 |ner-jave-zh|[damo/zh_ner-JAVE](https://modelscope.cn/datasets/damo/zh_ner-JAVE/summary)||1266|118.3±45.5, min=44, max=223|chat, ner|-|
 |coco-en|[modelscope/coco_2014_caption](https://modelscope.cn/datasets/modelscope/coco_2014_caption/summary)|coco_2014_caption|454617|299.8±2.8, min=295, max=352|chat, multi-modal, vision|-|

diff --git a/docs/source_en/LLM/Supported-models-datasets.md b/docs/source_en/LLM/Supported-models-datasets.md
@@ -216,6 +216,10 @@ The table below introcudes all models supported by SWIFT:
 |gemma-7b|[AI-ModelScope/gemma-7b](https://modelscope.cn/models/AI-ModelScope/gemma-7b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-7b](https://huggingface.co/google/gemma-7b)|
 |gemma-2b-instruct|[AI-ModelScope/gemma-2b-it](https://modelscope.cn/models/AI-ModelScope/gemma-2b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it)|
 |gemma-7b-instruct|[AI-ModelScope/gemma-7b-it](https://modelscope.cn/models/AI-ModelScope/gemma-7b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.38|-|[google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it)|
+|gemma2-9b|[LLM-Research/gemma-2-9b](https://modelscope.cn/models/LLM-Research/gemma-2-9b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b)|
+|gemma2-27b|[LLM-Research/gemma-2-27b](https://modelscope.cn/models/LLM-Research/gemma-2-27b/summary)|q_proj, k_proj, v_proj|default-generation|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-27b](https://huggingface.co/google/gemma-2-27b)|
+|gemma2-9b-instruct|[LLM-Research/gemma-2-9b-it](https://modelscope.cn/models/LLM-Research/gemma-2-9b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it)|
+|gemma2-27b-instruct|[LLM-Research/gemma-2-27b-it](https://modelscope.cn/models/LLM-Research/gemma-2-27b-it/summary)|q_proj, k_proj, v_proj|gemma|&#x2714;|&#x2714;|transformers>=4.42|-|[google/gemma-2-27b-it](https://huggingface.co/google/gemma-2-27b-it)|
 |minicpm-1b-sft-chat|[OpenBMB/MiniCPM-1B-sft-bf16](https://modelscope.cn/models/OpenBMB/MiniCPM-1B-sft-bf16/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;|transformers>=4.36.0|-|[openbmb/MiniCPM-1B-sft-bf16](https://huggingface.co/openbmb/MiniCPM-1B-sft-bf16)|
 |minicpm-2b-sft-chat|[OpenBMB/MiniCPM-2B-sft-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-sft-fp32/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;||-|[openbmb/MiniCPM-2B-sft-fp32](https://huggingface.co/openbmb/MiniCPM-2B-sft-fp32)|
 |minicpm-2b-chat|[OpenBMB/MiniCPM-2B-dpo-fp32](https://modelscope.cn/models/OpenBMB/MiniCPM-2B-dpo-fp32/summary)|q_proj, k_proj, v_proj|minicpm|&#x2714;|&#x2714;||-|[openbmb/MiniCPM-2B-dpo-fp32](https://huggingface.co/openbmb/MiniCPM-2B-dpo-fp32)|
@@ -416,6 +420,7 @@ The table below introduces the datasets supported by SWIFT:
 |webnovel-zh|[AI-ModelScope/webnovel_cn](https://modelscope.cn/datasets/AI-ModelScope/webnovel_cn/summary)||50000|1478.9±11526.1, min=100, max=490484|chat, novel|[zxbsmk/webnovel_cn](https://huggingface.co/datasets/zxbsmk/webnovel_cn)|
 |generated-chat-zh|[AI-ModelScope/generated_chat_0.4M](https://modelscope.cn/datasets/AI-ModelScope/generated_chat_0.4M/summary)||396004|273.3±52.0, min=32, max=873|chat, character-dialogue|[BelleGroup/generated_chat_0.4M](https://huggingface.co/datasets/BelleGroup/generated_chat_0.4M)|
 |🔥self-cognition|[swift/self-cognition](https://modelscope.cn/datasets/swift/self-cognition/summary)||134|53.6±18.6, min=29, max=121|chat, self-cognition|[modelscope/self-cognition](https://huggingface.co/datasets/modelscope/self-cognition)|
+|🔥swift-mix|[swift/swift-sft-mixture](https://modelscope.cn/datasets/swift/swift-sft-mixture/summary)|sharegpt<br>firefly<br>codefuse<br>metamathqa|-|Dataset is too huge, please click the original link to view the dataset stat.|chat, sft, general|-|
 |cls-fudan-news-zh|[damo/zh_cls_fudan-news](https://modelscope.cn/datasets/damo/zh_cls_fudan-news/summary)||4959|3234.4±2547.5, min=91, max=19548|chat, classification|-|
 |ner-jave-zh|[damo/zh_ner-JAVE](https://modelscope.cn/datasets/damo/zh_ner-JAVE/summary)||1266|118.3±45.5, min=44, max=223|chat, ner|-|
 |coco-en|[modelscope/coco_2014_caption](https://modelscope.cn/datasets/modelscope/coco_2014_caption/summary)|coco_2014_caption|454617|299.8±2.8, min=295, max=352|chat, multi-modal, vision|-|

diff --git a/swift/llm/data/dataset_info.json b/swift/llm/data/dataset_info.json
@@ -726,5 +726,11 @@
         "hf_dataset_id": "modelscope/self-cognition",
         "remove_useless_columns": false,
         "tags": ["chat", "self-cognition", "🔥"]
+    },
+    "swift-mix": {
+        "dataset_id": "swift/swift-sft-mixture",
+        "subsets": ["sharegpt", "firefly", "codefuse", "metamathqa"],
+        "tags": ["chat", "sft", "general", "🔥"],
+        "huge_dataset": true
     }
 }
diff --git a/swift/llm/utils/dataset.py b/swift/llm/utils/dataset.py
@@ -129,6 +129,7 @@ class DatasetName:
     webnovel_zh = 'webnovel-zh'
     generated_chat_zh = 'generated-chat-zh'
     self_cognition = 'self-cognition'
+    swift_mix = 'swift-mix'
 
     # example dataset for specific model
     cls_fudan_news_zh = 'cls-fudan-news-zh'  # seqgpt-560m

diff --git a/swift/llm/utils/model.py b/swift/llm/utils/model.py
@@ -291,6 +291,10 @@ class ModelType:
     gemma_7b = 'gemma-7b'
     gemma_2b_instruct = 'gemma-2b-instruct'
     gemma_7b_instruct = 'gemma-7b-instruct'
+    gemma2_9b = 'gemma2-9b'
+    gemma2_27b = 'gemma2-27b'
+    gemma2_9b_instruct = 'gemma2-9b-instruct'
+    gemma2_27b_instruct = 'gemma2-27b-instruct'
     # paligemma
     paligemma_3b_pt_224 = 'paligemma-3b-pt-224'
     paligemma_3b_pt_448 = 'paligemma-3b-pt-448'
@@ -1532,6 +1536,42 @@ def _output_device_map_hook(module, input, output):
     return model, tokenizer
 
 
+@register_model(
+    ModelType.gemma2_9b,
+    'LLM-Research/gemma-2-9b',
+    LoRATM.llama,
+    TemplateType.default_generation,
+    requires=['transformers>=4.42'],
+    support_flash_attn=True,
+    support_vllm=True,
+    hf_model_id='google/gemma-2-9b')
+@register_model(
+    ModelType.gemma2_27b,
+    'LLM-Research/gemma-2-27b',
+    LoRATM.llama,
+    TemplateType.default_generation,
+    requires=['transformers>=4.42'],
+    support_flash_attn=True,
+    support_vllm=True,
+    hf_model_id='google/gemma-2-27b')
+@register_model(
+    ModelType.gemma2_9b_instruct,
+    'LLM-Research/gemma-2-9b-it',
+    LoRATM.llama,
+    TemplateType.gemma,
+    requires=['transformers>=4.42'],
+    support_flash_attn=True,
+    support_vllm=True,
+    hf_model_id='google/gemma-2-9b-it')
+@register_model(
+    ModelType.gemma2_27b_instruct,
+    'LLM-Research/gemma-2-27b-it',
+    LoRATM.llama,
+    TemplateType.gemma,
+    requires=['transformers>=4.42'],
+    support_flash_attn=True,
+    support_vllm=True,
+    hf_model_id='google/gemma-2-27b-it')
 @register_model(
     ModelType.qwen2_57b_a14b,
     'qwen/Qwen2-57B-A14B',