huggingface/smol-course
Dec 2024 – Dec 2024
1 Month active
Languages Used
JSONJupyter NotebookMarkdownPython
Technical Skills
DPOData PreparationData ProcessingDeep LearningDocumentationHugging Face Transformers
David Quispe
PROFILE
David Quispe
During December 2024, Da Qc enhanced the huggingface/smol-course repository by developing localization-focused workflows and reorganizing core materials to improve accessibility for Spanish-speaking users. They delivered new Jupyter Notebooks and chat templates for SmolLM2, enabling streamlined supervised fine-tuning and dataset preparation. Leveraging Python and Hugging Face Transformers, Da Qc implemented Direct Preference Optimization (DPO) and Odds Ratio Preference Optimization (ORPO) tutorials with Spanish translations, and authored parameter-efficient fine-tuning (PEFT) documentation in Spanish. Their work included a comprehensive repository refactor, updated READMEs, and technical writing, resulting in more maintainable code and faster onboarding for non-English machine learning practitioners.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
16Total
Bugs
0
Commits
16
Features
5
Lines of code
31,536
Activity Months1
Work History
December 2024
16 Commits • 5 Features
Dec 1, 2024December 2024 monthly summary for huggingface/smol-course: Delivered localization-focused enhancements and notebook workflows for SmolLM2, expanding accessibility and facilitating supervised fine-tuning. Implemented and organized chat templates, added DPO/ORPO notebooks with EN-ES translations, produced PEFT/LoRA Spanish documentation, updated course READMEs and localizations, and completed a repository refactor to improve maintainability. No critical bugs reported; improvements enhance time-to-value for non-English users and streamline SFT datasets and training workflows, underscoring business value and technical excellence.
16 Commits • 5 Features
Dec 1, 2024December 2024 monthly summary for huggingface/smol-course: Delivered localization-focused enhancements and notebook workflows for SmolLM2, expanding accessibility and facilitating supervised fine-tuning. Implemented and organized chat templates, added DPO/ORPO notebooks with EN-ES translations, produced PEFT/LoRA Spanish documentation, updated course READMEs and localizations, and completed a repository refactor to improve maintainability. No critical bugs reported; improvements enhance time-to-value for non-English users and streamline SFT datasets and training workflows, underscoring business value and technical excellence.
December 2024
Activity
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Quality Metrics
Correctness98.8%
Maintainability98.8%
Architecture98.8%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
DPOData PreparationData ProcessingDeep LearningDocumentationHugging Face TransformersJupyter NotebooksLoRALocalizationMachine LearningModel Fine-tuningNatural Language ProcessingORPOParameter-Efficient Fine-Tuning (PEFT)Prefix Tuning
Repositories Contributed To
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