dice-group/dice-embeddings
Mar 2025 – Oct 2025
2 Months active
Languages Used
Python
Technical Skills
Code CleanupDebuggingDeep LearningMachine LearningPyTorchBug Fixing
Louis-Mozart
PROFILE
Louis-mozart
Worked on the dice-embeddings repository, focusing on enhancing the stability and reliability of deep learning pipelines for embedding models. Over two months, addressed critical bugs in negative sampling dimensionality and internal sigma computations, ensuring correct tensor shapes and stable model training. Improved data preprocessing by refactoring file handling logic to robustly detect and process diverse dataset formats, reducing edge-case failures during ingestion. Prioritized production hygiene by cleaning up debug artifacts and streamlining code paths, which improved maintainability without altering core behaviors. Leveraged Python, PyTorch, and OS utilities to deliver targeted improvements that strengthened both training workflows and inference reliability.
Overall Statistics
Feature vs Bugs
25%Features
Repository Contributions
4Total
Bugs
3
Commits
4
Features
1
Lines of code
57
Activity Months2
Your Network
9 peopleShared Repositories
9
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Caglar DemirMember
DuygubirolMember
Jean-KOUAGOUMember
Luke FriedrichsMember
sapkotaruz11Member
Shivam SharmaMember
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025 performance summary for the dice-embeddings repository. Focused on stabilizing training workflows and improving data ingestion robustness to support broader data formats and reliable model iteration cycles.
2 Commits • 1 Features
Oct 1, 2025October 2025 performance summary for the dice-embeddings repository. Focused on stabilizing training workflows and improving data ingestion robustness to support broader data formats and reliable model iteration cycles.
October 2025
March 2025
2 Commits
Mar 1, 2025March 2025: Focused on stability and correctness in the dice-embeddings repository. No feature releases; main value delivered through targeted bug fixes and production hygiene improvements that reduce risk in training and inference pipelines, enhancing the reliability of embeddings.
March 2025
2 Commits
Mar 1, 2025March 2025: Focused on stability and correctness in the dice-embeddings repository. No feature releases; main value delivered through targeted bug fixes and production hygiene improvements that reduce risk in training and inference pipelines, enhancing the reliability of embeddings.
Activity
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Quality Metrics
Correctness85.0%
Maintainability90.0%
Architecture85.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Bug FixingCode CleanupData PreprocessingDebuggingDeep LearningFile HandlingMachine LearningModel TrainingPyTorch
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