bump version to v0.6.1

README.md

@@ -149,7 +149,7 @@ For detailed inference benchmarks in more devices and more settings, please refe
   <li>InternLM-XComposer2 (7B, 4khd-7B)</li>
   <li>InternLM-XComposer2.5 (7B)</li>
   <li>Qwen-VL (7B)</li>
-  <li>Qwen2-VL (2B, 7B)</li>
+  <li>Qwen2-VL (2B, 7B, 72B)</li>
   <li>DeepSeek-VL (7B)</li>
   <li>InternVL-Chat (v1.1-v1.5)</li>
   <li>InternVL2 (1B-76B)</li>

README_zh-CN.md

@@ -150,7 +150,7 @@ LMDeploy TurboMind 引擎拥有卓越的推理能力，在各种规模的模型
   <li>InternLM-XComposer2 (7B, 4khd-7B)</li>
   <li>InternLM-XComposer2.5 (7B)</li>
   <li>Qwen-VL (7B)</li>
-  <li>Qwen2-VL (2B, 7B)</li>
+  <li>Qwen2-VL (2B, 7B, 72B)</li>
   <li>DeepSeek-VL (7B)</li>
   <li>InternVL-Chat (v1.1-v1.5)</li>
   <li>InternVL2 (1B-76B)</li>

docs/en/get_started/installation.md

@@ -23,7 +23,7 @@ pip install lmdeploy
 The default prebuilt package is compiled on **CUDA 12**. If CUDA 11+ (>=11.3) is required, you can install lmdeploy by:
 
 ```shell
-export LMDEPLOY_VERSION=0.6.0
+export LMDEPLOY_VERSION=0.6.1
 export PYTHON_VERSION=38
 pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
 ```

docs/en/supported_models/supported_models.md

@@ -20,6 +20,7 @@ The following tables detail the models supported by LMDeploy's TurboMind engine
 |         Qwen2         | 1.5B - 72B  | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |
 |        Mistral        |     7B      | LLM  |    Yes    |   Yes   |   Yes   |   -   |
 |        Qwen-VL        |     7B      | MLLM |    Yes    |   Yes   |   Yes   |  Yes  |
+|       Qwen2-VL        | 2B, 7B, 72B | MLLM |    Yes    |   Yes   |   Yes   |   -   |
 |      DeepSeek-VL      |     7B      | MLLM |    Yes    |   Yes   |   Yes   |  Yes  |
 |       Baichuan        |     7B      | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |
 |       Baichuan2       |     7B      | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |

docs/zh_cn/get_started/installation.md

@@ -23,7 +23,7 @@ pip install lmdeploy
 默认的预构建包是在 **CUDA 12** 上编译的。如果需要 CUDA 11+ (>=11.3)，你可以使用以下命令安装 lmdeploy：
 
 ```shell
-export LMDEPLOY_VERSION=0.6.0
+export LMDEPLOY_VERSION=0.6.1
 export PYTHON_VERSION=38
 pip install https://github.com/InternLM/lmdeploy/releases/download/v${LMDEPLOY_VERSION}/lmdeploy-${LMDEPLOY_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux2014_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
 ```

docs/zh_cn/supported_models/supported_models.md

@@ -20,6 +20,7 @@
 |         Qwen2         | 1.5B - 72B  | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |
 |        Mistral        |     7B      | LLM  |    Yes    |   Yes   |   Yes   |   -   |
 |        Qwen-VL        |     7B      | MLLM |    Yes    |   Yes   |   Yes   |  Yes  |
+|       Qwen2-VL        | 2B, 7B, 72B | MLLM |    Yes    |   Yes   |   Yes   |   -   |
 |      DeepSeek-VL      |     7B      | MLLM |    Yes    |   Yes   |   Yes   |  Yes  |
 |       Baichuan        |     7B      | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |
 |       Baichuan2       |     7B      | LLM  |    Yes    |   Yes   |   Yes   |  Yes  |

lmdeploy/version.py

@@ -1,7 +1,7 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 from typing import Tuple
 
-__version__ = '0.6.0'
+__version__ = '0.6.1'
 short_version = __version__