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
Contributed to the huggingface/smol-course repository by delivering five new features focused on localization and fine-tuning workflows for SmolLM2. Developed and organized Jupyter Notebooks for chat template usage, supervised fine-tuning, and preference optimization, with all materials and documentation translated into Spanish to expand accessibility. Leveraged Python and Hugging Face Transformers to implement DPO and ORPO tutorials, as well as parameter-efficient fine-tuning methods such as LoRA and PEFT. Refactored the repository structure to improve maintainability and updated core course materials, ensuring streamlined dataset preparation and training processes for non-English users. No critical bugs were reported during this period.
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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