vllm - 💡(How to fix) Fix [Bug]: Weight loading for meta-llama/Llama-4-Scout-17B-16E-Instruct is extremely slow [1 participants]

TL;DR

Optimizing the loading process for large models like meta-llama/Llama-4-Scout-17B-16E-Instruct may require adjustments to the data parallelism settings or the use of more efficient loading mechanisms.

Guidance

• Review the data_parallel.py script to understand how the model is being loaded and if there are any optimizations that can be applied to the loading process.
• Consider reducing the model size or using a more efficient model to speed up the loading process.
• Experiment with different all2all-backend options to see if an alternative approach can improve performance.
• Verify if the issue persists when running the script with a smaller model or fewer data parallelism settings.

Example

No specific code example can be provided without modifying the existing data_parallel.py script, but users can try adjusting the -dp and -tp flags to see if different parallelism settings improve performance.

Notes

The provided information does not specify the exact hardware or software environment, which could impact the performance of the model loading process. Additionally, the optimal solution may depend on the specific requirements of the project, such as the need for high accuracy versus fast inference times.

Recommendation

Apply workaround: Adjust the data parallelism settings or experiment with different all2all-backend options to find a configuration that balances performance and accuracy for the specific use case.