support qwen2-audio (modelscope#1633)

README.md

@@ -55,6 +55,7 @@ You can contact us and communicate with us by adding our group:
 <img src="asset/discord_qr.jpg" width="200" height="200">  |  <img src="asset/wechat.png" width="200" height="200">
 
 ## 🎉 News
+- 🔥2024.08.09: Support for inference and fine-tuning of the qwen2-audio model. Best practice can be found [here](https://github.com/modelscope/ms-swift/issues/1653).
 - 🔥2024.08.08: Supports the qwen2-math series models: 1.5B, 7B, 72B. Use `swift infer --model_type qwen2-math-1_5b-instruct` for an experience.
 - 🔥2024.08.07: Support for using vLLM for accelerating inference and deployment of multimodal large models such as the llava series and phi3-vision models. You can refer to the [Multimodal & vLLM Inference Acceleration Documentation](docs/source_en/Multi-Modal/vllm-inference-acceleration.md) for more information.
 - 2024.08.06: Support for minicpm-v-v2_6-chat is available. You can use `swift infer --model_type minicpm-v-v2_6-chat` for inference experience. Best practices can be found [here](https://github.com/modelscope/swift/issues/1613).
@@ -609,7 +610,7 @@ The complete list of supported models and datasets can be found at [Supported Mo
 | Model Type                                              | Model Introduction                                                                     | Language           | Model Size                            | Model Type               |
 |---------------------------------------------------------|----------------------------------------------------------------------------------------|--------------------|---------------------------------------|--------------------------|
 | Qwen-VL                                                 | [Tongyi Qwen vision model](https://github.com/QwenLM)                                  | Chinese<br>English | 7B<br>including quantized versions    | base model<br>chat model |
-| Qwen-Audio                                              | [Tongyi Qwen speech model](https://github.com/QwenLM)                                  | Chinese<br>English | 7B                                    | base model<br>chat model |
+| Qwen-Audio<br>Qwen2-Audio                           | [Tongyi Qwen speech model](https://github.com/QwenLM)                                  | Chinese<br>English | 7B                                    | base model<br>chat model |
 | YI-VL                                                   | [01AI's YI series vision models](https://github.com/01-ai)                             | Chinese<br>English | 6B-34B                                | chat model               |
 | XComposer2<br>XComposer2.5                              | [Pujiang AI Lab InternLM vision model](https://github.com/InternLM/InternLM-XComposer) | Chinese<br>English | 7B                                    | chat model               |
 | DeepSeek-VL                                             | [DeepSeek series vision models](https://github.com/deepseek-ai)                        | Chinese<br>English | 1.3B-7B                               | chat model               |

README_CN.md

@@ -56,6 +56,7 @@ SWIFT具有丰富全面的文档，请查看我们的文档网站:
 
 
 ## 🎉 新闻
+- 🔥2024.08.09: 支持qwen2-audio模型的推理与微调. 最佳实践可以查看[这里](https://github.com/modelscope/ms-swift/issues/1653).
 - 🔥2024.08.08: 支持qwen2-math系列模型, 1.5B, 7B, 72B. 使用`swift infer --model_type qwen2-math-1_5b-instruct`进行体验.
 - 🔥2024.08.07: 支持使用vllm对多模态大模型: llava系列, internvl2系列, phi3-vision, minicpm-v2.5进行推理加速和部署. 可以查看[多模态&vLLM推理加速文档](docs/source/Multi-Modal/vLLM推理加速文档.md)获取更多信息.
 - 2024.08.06: 支持minicpm-v-v2_6-chat, 使用`swift infer --model_type minicpm-v-v2_6-chat`进行推理体验, 最佳实践可以查看[这里](https://github.com/modelscope/swift/issues/1613).
@@ -603,7 +604,7 @@ CUDA_VISIBLE_DEVICES=0 swift deploy \
 | 模型类型                                                    | 模型介绍                                                                       | 语言       | 模型大小             | 模型类型             |
 |---------------------------------------------------------|----------------------------------------------------------------------------|----------|------------------|------------------|
 | Qwen-VL                                                 | [通义千问视觉模型](https://github.com/QwenLM)                                      | 中文<br>英文 | 7B<br>包含量化版本     | base模型<br>chat模型 |
-| Qwen-Audio                                              | [通义千问语音模型](https://github.com/QwenLM)                                      | 中文<br>英文 | 7B               | base模型<br>chat模型 |
+| Qwen-Audio<br>Qwen2-Audio                       | [通义千问语音模型](https://github.com/QwenLM)                                      | 中文<br>英文 | 7B               | base模型<br>chat模型 |
 | YI-VL                                                   | [01AI的YI系列视觉模型](https://github.com/01-ai)                                  | 中文<br>英文 | 6B-34B           | chat模型           |
 | XComposer2<br>XComposer2.5                              | [浦江实验室书生浦语视觉模型](https://github.com/InternLM/InternLM-XComposer)            | 中文<br>英文 | 7B               | chat模型           |
 | DeepSeek-VL                                             | [幻方系列视觉模型](https://github.com/deepseek-ai)                                 | 中文<br>英文 | 1.3B-7B          | chat模型           |

docs/source/LLM/VLLM推理加速与部署.md

@@ -2,6 +2,8 @@
 # VLLM推理加速与部署
 vllm支持的模型可以查看[支持的模型](支持的模型和数据集.md#模型).
 
+llama3.1 405b推理加速与部署最佳实践可以查看[这里](https://github.com/modelscope/ms-swift/issues/1484)
+
 ## 目录
 - [环境准备](#环境准备)
 - [推理加速](#推理加速)

docs/source/LLM/支持的模型和数据集.md

@@ -360,6 +360,8 @@
 |qwen-vl-chat-int4|[qwen/Qwen-VL-Chat-Int4](https://modelscope.cn/models/qwen/Qwen-VL-Chat-Int4/summary)|c_attn|qwen|✔|✘|✘|✘|auto_gptq>=0.5|vision|[Qwen/Qwen-VL-Chat-Int4](https://huggingface.co/Qwen/Qwen-VL-Chat-Int4)|
 |qwen-audio|[qwen/Qwen-Audio](https://modelscope.cn/models/qwen/Qwen-Audio/summary)|^(transformer.h)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|qwen-audio-generation|✔|✘|✘|✘||audio|[Qwen/Qwen-Audio](https://huggingface.co/Qwen/Qwen-Audio)|
 |qwen-audio-chat|[qwen/Qwen-Audio-Chat](https://modelscope.cn/models/qwen/Qwen-Audio-Chat/summary)|^(transformer.h)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|qwen-audio|✔|✘|✘|✘||audio|[Qwen/Qwen-Audio-Chat](https://huggingface.co/Qwen/Qwen-Audio-Chat)|
+|qwen2-audio-7b|[qwen/Qwen2-Audio-7B](https://modelscope.cn/models/qwen/Qwen2-Audio-7B/summary)|^(language_model\|multi_modal_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|qwen2-audio-generation|✔|✘|✘|✘|librosa|audio|[Qwen/Qwen2-Audio-7B](https://huggingface.co/Qwen/Qwen2-Audio-7B)|
+|qwen2-audio-7b-instruct|[qwen/Qwen2-Audio-7B-Instruct](https://modelscope.cn/models/qwen/Qwen2-Audio-7B-Instruct/summary)|^(language_model\|multi_modal_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|qwen2-audio|✔|✘|✘|✘|librosa|audio|[Qwen/Qwen2-Audio-7B-Instruct](https://huggingface.co/Qwen/Qwen2-Audio-7B-Instruct)|
 |glm4v-9b-chat|[ZhipuAI/glm-4v-9b](https://modelscope.cn/models/ZhipuAI/glm-4v-9b/summary)|^(transformer.encoder)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|glm4v|✘|✘|✘|✘|transformers>=4.42|vision|[THUDM/glm-4v-9b](https://huggingface.co/THUDM/glm-4v-9b)|
 |llava1_5-7b-instruct|[swift/llava-1.5-7b-hf](https://modelscope.cn/models/swift/llava-1.5-7b-hf/summary)|^(language_model\|multi_modal_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|llava1_5|✔|✔|✔|✘|transformers>=4.36|vision|[llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf)|
 |llava1_5-13b-instruct|[swift/llava-1.5-13b-hf](https://modelscope.cn/models/swift/llava-1.5-13b-hf/summary)|^(language_model\|multi_modal_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|llava1_5|✔|✔|✔|✘|transformers>=4.36|vision|[llava-hf/llava-1.5-13b-hf](https://huggingface.co/llava-hf/llava-1.5-13b-hf)|
@@ -377,9 +379,9 @@
 |yi-vl-6b-chat|[01ai/Yi-VL-6B](https://modelscope.cn/models/01ai/Yi-VL-6B/summary)|^(model.layers\|model.mm_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|yi-vl|✔|✘|✘|✘|transformers>=4.34|vision|[01-ai/Yi-VL-6B](https://huggingface.co/01-ai/Yi-VL-6B)|
 |yi-vl-34b-chat|[01ai/Yi-VL-34B](https://modelscope.cn/models/01ai/Yi-VL-34B/summary)|^(model.layers\|model.mm_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|yi-vl|✔|✘|✘|✘|transformers>=4.34|vision|[01-ai/Yi-VL-34B](https://huggingface.co/01-ai/Yi-VL-34B)|
 |llava-llama-3-8b-v1_1|[AI-ModelScope/llava-llama-3-8b-v1_1-transformers](https://modelscope.cn/models/AI-ModelScope/llava-llama-3-8b-v1_1-transformers/summary)|^(language_model\|multi_modal_projector)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|llava-llama-instruct|✔|✘|✔|✘|transformers>=4.36|vision|[xtuner/llava-llama-3-8b-v1_1-transformers](https://huggingface.co/xtuner/llava-llama-3-8b-v1_1-transformers)|
-|internlm-xcomposer2-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2-7b/summary)|^(model\|vision_proj)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internlm-xcomposer2|✘|✘|✔|✘||vision|[internlm/internlm-xcomposer2-7b](https://huggingface.co/internlm/internlm-xcomposer2-7b)|
-|internlm-xcomposer2-4khd-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2-4khd-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2-4khd-7b/summary)|^(model\|vision_proj)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internlm-xcomposer2-4khd|✘|✘|✔|✘||vision|[internlm/internlm-xcomposer2-4khd-7b](https://huggingface.co/internlm/internlm-xcomposer2-4khd-7b)|
-|internlm-xcomposer2_5-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2d5-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2d5-7b/summary)|^(model\|vision_proj)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internlm-xcomposer2_5|✔|✘|✔|✘||vision|[internlm/internlm-xcomposer2d5-7b](https://huggingface.co/internlm/internlm-xcomposer2d5-7b)|
+|internlm-xcomposer2-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2-7b/summary)|attention.wqkv, attention.wo, feed_forward.w1, feed_forward.w2, feed_forward.w3|internlm-xcomposer2|✘|✘|✔|✘||vision|[internlm/internlm-xcomposer2-7b](https://huggingface.co/internlm/internlm-xcomposer2-7b)|
+|internlm-xcomposer2-4khd-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2-4khd-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2-4khd-7b/summary)|attention.wqkv, attention.wo, feed_forward.w1, feed_forward.w2, feed_forward.w3|internlm-xcomposer2-4khd|✘|✘|✔|✘||vision|[internlm/internlm-xcomposer2-4khd-7b](https://huggingface.co/internlm/internlm-xcomposer2-4khd-7b)|
+|internlm-xcomposer2_5-7b-chat|[Shanghai_AI_Laboratory/internlm-xcomposer2d5-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-xcomposer2d5-7b/summary)|attention.wqkv, attention.wo, feed_forward.w1, feed_forward.w2, feed_forward.w3|internlm-xcomposer2_5|✔|✘|✔|✘|decord|vision|[internlm/internlm-xcomposer2d5-7b](https://huggingface.co/internlm/internlm-xcomposer2d5-7b)|
 |internvl-chat-v1_5|[AI-ModelScope/InternVL-Chat-V1-5](https://modelscope.cn/models/AI-ModelScope/InternVL-Chat-V1-5/summary)|^(language_model\|mlp1)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internvl|✔|✘|✔|✘|transformers>=4.35, timm|vision|[OpenGVLab/InternVL-Chat-V1-5](https://huggingface.co/OpenGVLab/InternVL-Chat-V1-5)|
 |internvl-chat-v1_5-int8|[AI-ModelScope/InternVL-Chat-V1-5-int8](https://modelscope.cn/models/AI-ModelScope/InternVL-Chat-V1-5-int8/summary)|^(language_model\|mlp1)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internvl|✔|✘|✘|✘|transformers>=4.35, timm|vision|[OpenGVLab/InternVL-Chat-V1-5-int8](https://huggingface.co/OpenGVLab/InternVL-Chat-V1-5-int8)|
 |mini-internvl-chat-2b-v1_5|[OpenGVLab/Mini-InternVL-Chat-2B-V1-5](https://modelscope.cn/models/OpenGVLab/Mini-InternVL-Chat-2B-V1-5/summary)|^(language_model\|mlp1)(?!.\*(lm_head\|output\|emb\|wte\|shared)).\*|internvl|✔|✘|✔|✘|transformers>=4.35, timm|vision|[OpenGVLab/Mini-InternVL-Chat-2B-V1-5](https://huggingface.co/OpenGVLab/Mini-InternVL-Chat-2B-V1-5)|

docs/source/Multi-Modal/index.md

@@ -11,7 +11,7 @@
 
 一轮对话可以包含多张图片（或不含图片）:
 1. [Qwen-VL最佳实践](qwen-vl最佳实践.md)
-2. [Qwen-Audio最佳实践](qwen-audio最佳实践.md)
+2. [Qwen-Audio最佳实践](qwen-audio最佳实践.md), [Qwen2-Audio最佳实践](https://github.com/modelscope/ms-swift/issues/1653)
 3. [Llava最佳实践](llava最佳实践.md), [LLava Video最佳实践](llava-video最佳实践.md)
 4. [InternVL系列最佳实践](internvl最佳实践.md)
 5. [Deepseek-VL最佳实践](deepseek-vl最佳实践.md)
@@ -26,4 +26,4 @@
 
 整个对话围绕一张图片（可能可以不含图片）:
 1. [CogVLM最佳实践](cogvlm最佳实践.md), [CogVLM2最佳实践](cogvlm2最佳实践.md), [glm4v最佳实践](glm4v最佳实践.md), [CogVLM2-Video最佳实践](cogvlm2-video最佳实践.md)
-2. [MiniCPM-V最佳实践](minicpm-v最佳实践.md), [MiniCPM-V-2最佳实践](minicpm-v-2最佳实践.md), [MiniCPM-V-2.5最佳实践](minicpm-v-2.5最佳实践.md)
+2. [MiniCPM-V最佳实践](minicpm-v最佳实践.md), [MiniCPM-V-2最佳实践](minicpm-v-2最佳实践.md), [MiniCPM-V-2.5最佳实践](minicpm-v-2.5最佳实践.md), [MiniCPM-V-2.6最佳实践](https://github.com/modelscope/ms-swift/issues/1613)

docs/source/Multi-Modal/minicpm-v-2.5最佳实践.md

@@ -1,6 +1,8 @@
 
 # MiniCPM-V-2.5 最佳实践
 
+MiniCPM-V-2.6 最佳实践: [https://github.com/modelscope/ms-swift/issues/1613](https://github.com/modelscope/ms-swift/issues/1613)
+
 ## 目录
 - [环境准备](#环境准备)
 - [推理](#推理)

docs/source/Multi-Modal/qwen-audio最佳实践.md

@@ -1,5 +1,7 @@
 # Qwen-Audio 最佳实践
 
+Qwen2-Audio的最佳实践可以查看: [https://github.com/modelscope/ms-swift/issues/1653](https://github.com/modelscope/ms-swift/issues/1653)
+
 ## 目录
 - [环境准备](#环境准备)
 - [推理](#推理)