ggml-org/llama.cpp
Jun 2025 – Jun 2025
1 Month active
Languages Used
C++Python
Technical Skills
C++ programmingPython programmingdeep learningmachine learningmodel architecture
Weizhao Ouyang
PROFILE
Weizhao Ouyang
Worked on integrating ERNIE 4.5 0.3B model support into the ggml-org/llama.cpp repository, focusing on expanding the framework’s compatibility with new deep learning architectures. The work involved defining the model architecture, modifying tensor structures, and ensuring seamless integration with the existing model workflow. Using C++ and Python, the developer aligned the new model variant with established framework conventions and testing harnesses to maintain consistency and reliability. The contribution enhanced deployment options for downstream applications by broadening model support. All changes were documented with clear, descriptive commits, providing traceability and rationale for future maintenance and collaborative development efforts.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
260
Activity Months1
Your Network
1056 peopleSame Organization
@arm.com573
Work History
June 2025
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focusing on delivering feature support and integrating new model variant into the existing llama.cpp framework. The primary deliverable was ERNIE 4.5 0.3B model support added to ggml-org/llama.cpp, including architecture definitions, tensor modifications, and full integration with the current model workflow. This enhances model compatibility and deployment options for customers and downstream applications.
1 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary focusing on delivering feature support and integrating new model variant into the existing llama.cpp framework. The primary deliverable was ERNIE 4.5 0.3B model support added to ggml-org/llama.cpp, including architecture definitions, tensor modifications, and full integration with the current model workflow. This enhances model compatibility and deployment options for customers and downstream applications.
June 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ programmingPython programmingdeep learningmachine learningmodel architecture
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