huggingface/peft
Jul 2025 – Jul 2025
1 Month active
Languages Used
MarkdownPythonShell
Technical Skills
Adapter-based Fine-tuningDeep LearningDocumentationLibrary IntegrationMachine LearningModel Implementation
kkb-code
PROFILE
Kkb-code
Developed and integrated the SHiRA Adapters feature into the huggingface/peft repository, introducing Sparse High Rank Adapters as a new parameter-efficient fine-tuning method for large language models. The work encompassed end-to-end implementation, including configuration design, model integration, comprehensive documentation, and example usage to support seamless adoption within existing workflows. Leveraged Python and Shell scripting to ensure robust library integration and maintainability. Focused on adapter-based fine-tuning and deep learning techniques, the contribution addressed the need for more efficient model adaptation, enabling users to fine-tune large models with reduced computational overhead while maintaining compatibility with the core PEFT library.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,632
Activity Months1
Your Network
299 peopleWork History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly performance summary for huggingface/peft. Delivered SHiRA Adapters as a new PEFT method, with configurations, model implementations, documentation, and example usage, integrated into the core PEFT library to enable more efficient fine-tuning of large language models.
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly performance summary for huggingface/peft. Delivered SHiRA Adapters as a new PEFT method, with configurations, model implementations, documentation, and example usage, integrated into the core PEFT library to enable more efficient fine-tuning of large language models.
July 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPythonShell
Technical Skills
Adapter-based Fine-tuningDeep LearningDocumentationLibrary IntegrationMachine LearningModel ImplementationParameter-Efficient Fine-Tuning (PEFT)
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