madeline-underwood/arm-learning-paths
Jul 2025 – Feb 2026
2 Months active
Languages Used
BashMarkdownPython
Technical Skills
DocumentationMobile Development SetupShell ScriptingData ProcessingDockerFine-tuning
Michael Hall
PROFILE
Michael Hall
Over two months, Michael Hall enhanced the madeline-underwood/arm-learning-paths repository by improving onboarding reproducibility and developing a robust fine-tuning workflow for large language models. He updated setup flows for Android and Ubuntu, refining shell scripts and documentation to streamline developer onboarding and workshop preparation. Leveraging Python, PyTorch, and Docker, Michael introduced a comprehensive guide for fine-tuning models on NVIDIA DGX Spark, integrating a new base model and custom dataset to improve accuracy. He also addressed compatibility issues by adding a tokenizer notice for legacy transformers, demonstrating attention to stability and maintainability in machine learning and mobile development environments.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
823
Activity Months2
Your Network
129 peopleWork History
February 2026
3 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for madeline-underwood/arm-learning-paths. Focused on delivering a refined model fine-tuning workflow and ensuring compatibility with legacy transformers to enhance stability and learning outcomes. Key features delivered include a comprehensive PyTorch fine-tuning guide for DGX Spark, learning-path updates using a forked script, and a base model update to LLama-3.2-3B-Instruct with a custom dataset to boost accuracy. A minor but critical bug fix introduced a tokenizer compatibility notice to maintain vLLM server functionality with older transformer versions.
3 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for madeline-underwood/arm-learning-paths. Focused on delivering a refined model fine-tuning workflow and ensuring compatibility with legacy transformers to enhance stability and learning outcomes. Key features delivered include a comprehensive PyTorch fine-tuning guide for DGX Spark, learning-path updates using a forked script, and a base model update to LLama-3.2-3B-Instruct with a custom dataset to boost accuracy. A minor but critical bug fix introduced a tokenizer compatibility notice to maintain vLLM server functionality with older transformer versions.
February 2026
July 2025
1 Commits • 1 Features
Jul 1, 2025Open Audio Small learning path prerequisites and setup flow enhancements for madeline-underwood/arm-learning-paths, focusing on onboarding reproducibility and workshop readiness. Implemented updated toolchain and setup instructions across Android and Ubuntu environments, enabling smoother execution for developers and partners. Commit e0352342c03cd41097194a22afc7bdafe07a8e00 documents the changes and was aligned with workshop preparation for WeAreDevelopers.
July 2025
1 Commits • 1 Features
Jul 1, 2025Open Audio Small learning path prerequisites and setup flow enhancements for madeline-underwood/arm-learning-paths, focusing on onboarding reproducibility and workshop readiness. Implemented updated toolchain and setup instructions across Android and Ubuntu environments, enabling smoother execution for developers and partners. Commit e0352342c03cd41097194a22afc7bdafe07a8e00 documents the changes and was aligned with workshop preparation for WeAreDevelopers.
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance85.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
BashMarkdownPython
Technical Skills
Data ProcessingDockerDocumentationFine-tuningMachine LearningMobile Development SetupNVIDIA DGXPyTorchPythonShell Scriptingdocumentationfine-tuningmachine learningtransformers
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