Qwen2 V L 72 B

Introduction

Qwen2-VL-72B is the latest iteration in the Qwen-VL series, showcasing nearly a year of advancements. This model is designed to deliver state-of-the-art performance in visual understanding, video comprehension, and multilingual support. It is the base pretrained model and does not include instruction tuning.

Architecture

Qwen2-VL-72B introduces several significant updates:

• Naive Dynamic Resolution: Capable of handling arbitrary image resolutions and mapping them into dynamic visual tokens for enhanced visual processing.
• Multimodal Rotary Position Embedding (M-ROPE): This feature decomposes positional embedding into components that manage 1D textual, 2D visual, and 3D video positional information, improving multimodal processing.

The repository includes the pretrained model consisting of 72 billion parameters.

Training

The model achieves state-of-the-art performance in visual understanding benchmarks such as MathVista, DocVQA, and RealWorldQA. It is capable of answering questions from videos over 20 minutes long and can be integrated with mobile and robotic devices for complex reasoning and decision-making tasks. Additionally, Qwen2-VL supports understanding of multiple languages within images, including most European languages, Japanese, Korean, Arabic, and Vietnamese.

Guide: Running Locally

1. Install Requirements: Ensure you have the latest version of Hugging Face's transformers library:

   pip install -U transformers
   

   Failure to update may result in a KeyError: 'qwen2_vl'.

2. Model Setup: Download and configure the Qwen2-VL-72B model from Hugging Face.

3. Optional Cloud Setup: For improved performance, consider using cloud GPU services such as AWS EC2, Google Cloud Platform, or Azure.

License

The Qwen2-VL-72B model is distributed under the Qwen license. The full license text can be accessed here.