madeline-underwood/arm-learning-paths
Mar 2025 – Mar 2025
1 Month active
Languages Used
BashMarkdownPython
Technical Skills
API IntegrationArm ArchitectureCloud ComputingLLM DeploymentMachine Learning
Tianyu Li
PROFILE
Tianyu Li
Developed a comprehensive learning path for deploying the DeepSeek R1 large language model on Arm CPUs within the madeline-underwood/arm-learning-paths repository. The work encompassed environment setup, building llama.cpp, model download and execution, and providing OpenAI-compatible API access, all tailored for Arm architecture. Focused on optimizing inference throughput and latency, the solution improved performance for machine learning workloads on Arm hardware. Leveraged Python and Bash to automate deployment steps and streamline onboarding for developers. This contribution expanded cross-architecture support and enabled broader hardware compatibility, addressing the need for efficient LLM deployment workflows in cloud computing and machine learning environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
519
Activity Months1
Your Network
672 peopleSame Organization
@arm.com538
Work History
March 2025
1 Commits • 1 Features
Mar 1, 2025Monthly summary for 2025-03 focusing on key accomplishments and business impact.
1 Commits • 1 Features
Mar 1, 2025Monthly summary for 2025-03 focusing on key accomplishments and business impact.
March 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
BashMarkdownPython
Technical Skills
API IntegrationArm ArchitectureCloud ComputingLLM DeploymentMachine Learning
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