volcengine/verl
Feb 2026 – Feb 2026
1 Month active
Languages Used
Pythonbashpython
Technical Skills
Data ProcessingDeep LearningMachine LearningPythonbash scriptingdeep learning
zhengxiaojun
PROFILE
Zhengxiaojun
Worked on the volcengine/verl repository to deliver two feature enhancements focused on model evaluation and training scalability for the Qwen3-VL family. Developed a ViT FLOPs calculation update by adding images_seqlens support in MFU, enabling more accurate resource planning and performance analytics. Also implemented NPU GRPO training scripts for Qwen3-VL-30B, integrating FSDP and VLLM backends to expand training options across hardware platforms. Employed Python and bash scripting to ensure robust CI hygiene and cross-backend compatibility. The work emphasized deep learning, data processing, and model training, with validation through comprehensive training curves and multi-backend test results.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
107
Activity Months1
Your Network
415 peopleWork History
February 2026
2 Commits • 2 Features
Feb 1, 2026February 2026: Delivered two major feature enhancements in volcengine/verl, expanding model evaluation capabilities and training scalability, while maintaining CI hygiene and cross-backend support. These efforts improve resource planning, deployment readiness, and performance analytics for Qwen3-VL family models.
2 Commits • 2 Features
Feb 1, 2026February 2026: Delivered two major feature enhancements in volcengine/verl, expanding model evaluation capabilities and training scalability, while maintaining CI hygiene and cross-backend support. These efforts improve resource planning, deployment readiness, and performance analytics for Qwen3-VL family models.
February 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Pythonbashpython
Technical Skills
Data ProcessingDeep LearningMachine LearningPythonbash scriptingdeep learningmachine learningmodel training
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