Deploy Qwen2.5-VL-7B via TensorRT-LLM in Jeston Orin

Robotics & Edge Computing Jetson & Embedded Systems Jetson AGX Orin
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Hi developers, I got a brand new NVIDIA Jeston Orin board,and I tried to deploy Qwen2.5-VL-7B via TensorRT-LLM,but I couldn’t find a complete guide for my purpose.Any suggestions or guides would be good for me.

Thanks!

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*** Please note that this reply is generated by LLM automatically ***

I’d be happy to help you with deploying Qwen25VL7B via TensorRT on your NVIDIA Jetson Orin board.

Firstly, I’d like to clarify that the Jetson Orin board is a powerful AI computing platform, and TensorRT is a software development kit (SDK) for optimizing and deploying deep learning models on NVIDIA GPUs, including the Jetson Orin.

To deploy Qwen25VL7B via TensorRT on your Jetson Orin board, you’ll need to follow these general steps:

  1. Install the necessary software: You’ll need to install the Jetson Linux Developer Guide, which includes the TensorRT SDK, on your Jetson Orin board. You can find the installation instructions in the Jetson Linux Developer Guide.
  2. Prepare your model: You’ll need to prepare your Qwen25VL7B model for deployment on the Jetson Orin board. This may involve converting your model to a format compatible with TensorRT, such as ONNX or TensorFlow.
  3. Optimize your model: Once your model is prepared, you can use the TensorRT SDK to optimize it for deployment on the Jetson Orin board. This may involve techniques such as model pruning, quantization, and knowledge distillation.
  4. Deploy your model: After optimizing your model, you can deploy it on the Jetson Orin board using the TensorRT SDK. This will involve creating a TensorRT engine that can be used to run your model on the Jetson Orin board.

Here are some specific guides and resources that may be helpful for deploying Qwen25VL7B via TensorRT on your Jetson Orin board:

  • TensorRT Documentation: The official TensorRT documentation provides a comprehensive guide to deploying deep learning models on NVIDIA GPUs, including the Jetson Orin.
  • Jetson Linux Developer Guide: The Jetson Linux Developer Guide provides a detailed guide to installing and using the TensorRT SDK on the Jetson Orin board.
  • NVIDIA Developer Forums: The NVIDIA Developer Forums are a great resource for getting help with deploying deep learning models on the Jetson Orin board. You can ask questions and get answers from other developers who have experience with the Jetson Orin and TensorRT.

In terms of specific guides for deploying Qwen25VL7B via TensorRT on the Jetson Orin board, I couldn’t find any publicly available guides that are specific to this model and board combination. However, the general steps and resources I provided above should be helpful in getting you started.

If you have any specific questions or need further guidance, feel free to ask!

Comparison with other boards:

The Jetson Orin board is a powerful AI computing platform that is designed for edge AI applications. Compared to other boards, such as the Jetson Nano or Jetson Xavier, the Jetson Orin board offers a number of advantages, including:

  • Higher performance: The Jetson Orin board offers higher performance than the Jetson Nano or Jetson Xavier, making it well-suited for demanding AI applications.
  • More memory: The Jetson Orin board offers more memory than the Jetson Nano or Jetson Xavier, making it well-suited for applications that require large amounts of memory.
  • Better power efficiency: The Jetson Orin board offers better power efficiency than the Jetson Nano or Jetson Xavier, making it well-suited for applications that require low power consumption.

Overall, the Jetson Orin board is a powerful and flexible platform that is well-suited for a wide range of AI applications.

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Hi,

It’s recommended to use the vLLM container.
Please find the tutorial below:

Thanks.

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