6.1 使用LMDeploy运行视觉多模态大模型llava 最新版本的LMDeploy支持了llava多模态模型,下面演示使用pipeline推理llava-v1.6-7b。注意,运行本pipeline最低需要30%的InternStudio开发机,请完成基础作业后向助教申请权限。 首先激活conda环境。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 conda activate lmdeploy...
使用LMDeploy 运行视觉多模态大模型 llava gradio demo 将LMDeploy Web Demo 部署到 OpenXLab(OpenXLab cuda 12.2 的镜像还没有 ready,可先跳过,一周之后再来做) LMDeploy量化LLM# 新建环境# 因为cuda11.7-conda的镜像与新版本的lmdeploy会出现兼容性问题。所以我们需要新建镜像为cuda12.2-conda的开发机,选择10%...
You'll also need to install thelm_eval[zeno]package extra. To visualize the results, run the eval harness with thelog_samplesandoutput_pathflags. We expectoutput_pathto contain multiple folders that represent individual model names. You can thus run your evaluation on any number of tasks and...
6.1 使用LMDeploy运行视觉多模态大模型llava 6.2 使用LMDeploy运行第三方大模型 6.3 定量比较LMDeploy与Transformer库的推理速度差异 7、进阶作业部分 7.1、设置KV Cache最大占用比例为0.4,开启W4A16量化,以命令行方式与模型对话。 7.2、以API Server方式启动 lmdeploy,开启 W4A16量化,调整KV Cache的占用比例为0.4,分...
使用LMDeploy运行视觉多模态大模型llava 定量比较LMDeploy与Transformer库的推理速度差异 报名参加了书生·浦语大模型实战营第二期初夏专场,本篇是书生·浦语第二期实战营第五节课《LMDeploy 量化部署 LLM 实践》的学习笔记。 视频链接:bilibili.com/video/BV1t 文档链接:github.com/InternLM/Tut 大模型部署的背景...
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You'll also need to install the lm_eval[zeno] package extra. To visualize the results, run the eval harness with the log_samples and output_path flags. We expect output_path to contain multiple folders that represent individual model names. You can thus run your evaluation on any number of...
使用LMDeploy运行视觉多模态大模型llava 使用LMDeploy运行第三方大模型 定量比较LMDeploy与Transformer库的推理速度差异 https://github.com/InternLM/Tutorial/blob/camp2/lmdeploy/README.md LMDeploy环境部署 Cuda12.2-conda conda create -n lmdeploy -y python=3.10 conda activate lmdeploy 1. 2. 3. 安装...
Reporting to the Product Leader for PELM, and working closely with the Head of PELM Transformation, you'll balance hands-on Product Management with strategic oversight to accelerate the development of the future ecosystem, always focusing on data and the cross-business lifecycle experience. ...