unslothai/unsloth-zoo
Apr 2026 – Apr 2026
1 Month active
Languages Used
Python
Technical Skills
Data ProcessingMachine LearningPython Programming
Maxime De Bruyn
PROFILE
Maxime De Bruyn
Maxime de Bruyn developed a targeted fine-tuning enhancement for the unsloth-zoo repository, enabling model training to focus specifically on the most recent assistant response. By introducing the last_response_only parameter and integrating it through the train_on_responses_only workflow and UnslothVisionDataCollator, Maxime ensured compatibility and maintained ABI stability for downstream components. The work involved end-to-end updates in Python, including adjustments to vision_utils.py and comprehensive documentation improvements. This feature streamlines data processing and machine learning workflows by reducing supervision overhead and improving response relevance, reflecting a thoughtful approach to API evolution and collaborative engineering with attention to integration quality.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
58
Activity Months1
Your Network
39 peopleShared Repositories
39
Work History
April 2026
1 Commits • 1 Features
Apr 1, 2026Month: 2026-04. In unsloth-zoo, delivered a targeted fine-tuning enhancement by focusing training on the most recent assistant response using a new last_response_only parameter. Implemented end-to-end changes across train_on_responses_only flow, wired through UnslothVisionDataCollator, and updated vision_utils.py. Added compatibility and clarity updates, updated docstrings, and ensured ABI stability by moving the new parameter to the end of the UnslothVisionDataCollator signature. Collaboration with Maxime and danielhanchen. Impact: improves the relevance of fine-tuned responses, reduces supervision overhead, and preserves stable integration for downstream components. Technologies demonstrated: Python, data collator design, model fine-tuning workflows, documentation discipline, ABI-safe API evolution.
1 Commits • 1 Features
Apr 1, 2026Month: 2026-04. In unsloth-zoo, delivered a targeted fine-tuning enhancement by focusing training on the most recent assistant response using a new last_response_only parameter. Implemented end-to-end changes across train_on_responses_only flow, wired through UnslothVisionDataCollator, and updated vision_utils.py. Added compatibility and clarity updates, updated docstrings, and ensured ABI stability by moving the new parameter to the end of the UnslothVisionDataCollator signature. Collaboration with Maxime and danielhanchen. Impact: improves the relevance of fine-tuned responses, reduces supervision overhead, and preserves stable integration for downstream components. Technologies demonstrated: Python, data collator design, model fine-tuning workflows, documentation discipline, ABI-safe API evolution.
April 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data ProcessingMachine LearningPython Programming
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