Rex-Omni 开始 - 技术栈

Rex-Omni 是一个 3B 参数多模态模型，它将视觉感知任务统一到一个"下一点预测"框架中。

主页: rex-omni.github.io/
代码: github.com/IDEA-Resear...

其支持的任务有：物体检测、OCR、指向、关键点定位、视觉提示。

官方 README 有详细说明，包括各任务的示例。以下是个人的实践手记 ✌️

环境

准备 Conda 环境，

bash 复制代码

conda create -n rexomni python=3.10 -y
conda activate rexomni

# Install PyTorch (CPU version)
pip install torch torchvision
# Install PyTorch with CUDA (version <= nvidia-smi shown)
#  https://pytorch.org/get-started/locally
pip install torch==2.7.0 torchvision --index-url https://download.pytorch.org/whl/cu128

准备 Rex-Omni，

bash 复制代码

git clone --depth 1 https://github.com/IDEA-Research/Rex-Omni.git
cd Rex-Omni
pip install -r requirements.txt
pip install -v -e .

如遇 flash-attn 安装错误，

bash 复制代码

# 直接安装预编译的 flash-attn
wget https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.7cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
pip install ./flash_attn-*.whl

# 或编译安装 flash-attn
#  https://github.com/dao-ailab/flash-attention
conda install -c nvidia cuda=12.8
# pip install -U pip setuptools
pip install packaging psutil ninja
MAX_JOBS=4 pip install flash-attn --no-build-isolation

# 检查 flash-attn 版本（注意版本要求）
#  Rex-Omni: flash-attn==2.7.4.post1
#  xformers: flash-attn>=2.7.1,<=2.7.4
python -c "import flash_attn; print(flash_attn.__version__)"

推理

bash 复制代码

# Use model: Rex-Omni-AWQ, not Rex-Omni
#  vLLM params adjusted to reduce HBM usage
HF_ENDPOINT=https://hf-mirror.com python practice/Rex-Omni/infer_awq.py
# HF_ENDPOINT=https://hf-mirror.com python practice/Rex-Omni/infer.py

# Notice:
#  Cannot use FlashAttention-2 backend for Volta and Turing GPUs

代码，

infer_awq.py

结果，

训练

Fine-tuning Guide

结语

Let's Go Coding ~