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A high-throughput and memory-efficient inference and serving engine for LLMs - GitHub - ywang96/vllm at qwen2_5_vl
Collaborator yixqiao commented Feb 1, 2025 • edited by github-actions bot Add the new ViT class in vLLM to Qwen 2.5 VL, removing the huggingface pretrained dependency. Includes changes to MLP, window-based partial attention, RMSNorm, when compared to 2 VL. Enables parallelized operations ...
Use PEFT or Full-parameter to finetune 500+ LLMs (Qwen2.5, InternLM3, GLM4, Llama3.3, Mistral, Yi1.5, DeepSeek-R1, ...) and 200+ MLLMs (Qwen2.5-VL, Qwen2.5-Omni, Qwen2-Audio, Llama3.2-Vision, Llava, InternVL2.5, MiniCPM-V-2.6, GLM4v, Xcomposer2.5, DeepSe
pip install git+https://github.com/huggingface/transformers accelerate or you might encounter the following error: KeyError: 'qwen2_5_vl' We offer a toolkit to help you handle various types of visual input more conveniently, as if you were using an API. This includes base64, URLs, and int...
更多详细信息见 Github 仓库。 二、部署过程 基础环境最低要求说明: 1. 更新基础软件包 查看系统版本信息 # 查看系统版本信息,包括ID(如ubuntu、centos等)、版本号、名称、版本号ID等 cat /etc/os-release 配置apt 国内源 # 更新软件包列表 apt-getupdate ...
安装与Qwen2-VL微调相关的第三方库,可以使用以下命令: pip install modelscope transformers sentencepiece accelerate datasets peft swanlab qwen-vl-utils pandas 2. 数据准备 依次执行: 3. 开始微调 此时的目录结构为: |——— train.py |——— data2csv.py |——— csv2json.py |——— latex_ocr_...
Github链接:https://github.com/QwenLM/Qwen2-VL 亮点直击 本文介绍了Qwen系列大型视觉语言模型的最新成员:Qwen2-VL系列,该系列包括三款开放权重模型,总参数量分别为20亿、80亿和720亿。如图1所示,Qwen2-VL的关键进展包括: 在各种分辨率和宽高比上的最先进理解能力:Qwen2-VL在视觉基准测试中表现出色,包括DocVQA、...
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github-actionsbotadded thependinglabelOct 19, 2024 Copy link Author commentedOct 20, 2024 同样问题。现在只能用预训练的qwen/Qwen2-VL-7B-Instruct的processor,然后weight用自己的local file 我现在用的方法如下,运行后看起来没问题,不过不知道对不对,是否正确加载了微调后的权重。