vllm-project/llm-compressor
Mar 2026 – Mar 2026
1 Month active
Languages Used
Python
Technical Skills
Deep LearningMachine LearningPyTorchPythonPython programmingQuantization
Gilles Turpin
PROFILE
Gilles Turpin
Worked on the vllm-project/llm-compressor repository to enhance model compatibility and deployment reliability for deep learning workflows. Focused on improving quantization robustness and interoperability across GLM-5, DeepSeek, and FX tracing by refining mapping registries and updating regex patterns for accurate layer recognition. Addressed stability issues in FX tracing by enforcing correct topological order during graph cleanup, reducing runtime risk. Resolved quantization shape mismatches by precomputing packed weight and scale shapes, supporting diverse quantization configurations. Leveraged Python, PyTorch, and algorithm design skills to deliver features and fixes, with comprehensive unit testing to ensure quality and maintainability across evolving model architectures.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
2
Lines of code
180
Activity Months1
Your Network
66 peopleShared Repositories
66
Work History
March 2026
4 Commits • 2 Features
Mar 1, 2026In March 2026, delivered significant feature improvements, stability fixes, and quantization enhancements for vllm-project/llm-compressor, driving interoperability, performance, and reliability across GLM-5, DeepSeek, and FX tracing workflows. The work emphasizes business value through better model compatibility, smoother deployment, and reduced runtime risk.
4 Commits • 2 Features
Mar 1, 2026In March 2026, delivered significant feature improvements, stability fixes, and quantization enhancements for vllm-project/llm-compressor, driving interoperability, performance, and reliability across GLM-5, DeepSeek, and FX tracing workflows. The work emphasizes business value through better model compatibility, smoother deployment, and reduced runtime risk.
March 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Deep LearningMachine LearningPyTorchPythonPython programmingQuantizationalgorithm designback end developmentregexsoftware testing
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