Errors and Troubleshooting for NanoVLM Tutorial on Jetson Orin Nano

Issue Overview

Several users have reported encountering various errors when following the "NanoVLM – Efficient Multimodal Pipeline" tutorial on the Jetson Orin Nano (8GB) with a 128GB SD card. The issues occur when running the jetson-containers command with different model flags, each resulting in a specific error.

The main problems include:

• Exception during the MLC quantization process for the VILA1.5-3b model, stating "The model config should have continued information about maximum sequence length"
• Download interruption and lack of access to "force_download" and "resume_download" parameters for the Obsidian-3B model
• Internal error after entering an image file path and question for the Llava-7b model

These errors prevent users from successfully completing the tutorial and utilizing the NanoVLM pipeline on their Jetson Orin Nano devices.

Possible Causes

1. Incompatible or outdated container image: The errors may occur due to using an incompatible or outdated version of the nano_llm container image.

2. Missing model configuration: For the VILA1.5-3b model, the error suggests that the model configuration file lacks necessary information about the maximum sequence length, leading to the exception during quantization.

3. Unstable model download: The interruption in downloading the Obsidian-3B model could be caused by instability or temporary issues with the Hugging Face server hosting the model files.

4. Insufficient memory or storage: The internal error encountered with the Llava-7b model might be related to insufficient memory or storage resources on the Jetson Orin Nano device.

5. Software version incompatibilities: Differences in JetPack or L4T versions between the tutorial environment and the user’s setup could lead to compatibility issues and errors.

Troubleshooting Steps, Solutions & Fixes

1. Update the nano_llm container image:

   • Pull the latest version of the nano_llm container image by running:

     sudo docker pull dustynv/nano_llm:r35.4.1
     

   • If using JetPack 5, try the newer tag:

     sudo docker pull dustynv/nano_llm:24.5.1-r35.4.1
     

2. Delete problematic model directories:

   • Remove the directory for models that encountered download issues or errors, such as:

     rm -rf /data/models/huggingface/models--Efficient-Large-Model--VILA1.5-3b
     

   • Retry running the jetson-containers command with the corresponding model flag after deleting the directory.

3. Verify storage space and memory availability:

   • Ensure that sufficient storage space is available on the SD card or device storage.
   • Monitor memory usage during the tutorial steps and close any unnecessary applications to free up memory resources.

4. Check JetPack and L4T versions:

   • Confirm that you are using a compatible version of JetPack and L4T as mentioned in the tutorial or by the community.
   • Consider updating to the latest stable versions of JetPack and L4T if possible.

5. Retry with alternative models:

   • If issues persist with a specific model, attempt the tutorial steps with a different model that has been successfully used by other community members.

6. Seek community support:

   • Engage with the Jetson and NanoVLM communities on forums or discussion platforms to seek further guidance and troubleshooting assistance from experienced users and developers.

If the above steps do not resolve the issues, provide detailed information about your setup, versions, and error messages to the community or tutorial authors for further investigation and support.