EvolvingLMMs-Lab/lmms-eval
May 2026 – May 2026
1 Month active
Languages Used
PythonYAML
Technical Skills
Python programmingconfiguration managementdata processingmachine learning
Tanush Yadav
PROFILE
Tanush Yadav
Developed and integrated the VideoNet benchmark into the lmms-eval evaluation framework, focusing on expanding benchmarking capabilities and improving workflow efficiency. Leveraged Python and YAML to implement selective data download logic, ensuring only necessary files were fetched, which reduced both data transfer and storage requirements. Added new configuration files and utility functions to streamline integration and support reproducible evaluation tasks. This work enhanced the speed and reliability of model evaluation, enabling faster iteration and clearer performance comparisons. The contributions to the EvolvingLMMs-Lab/lmms-eval repository demonstrated strong skills in Python programming, configuration management, and data processing within machine learning workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
322
Activity Months1
Your Network
95 peopleWork History
May 2026
1 Commits • 1 Features
May 1, 2026Delivered VideoNet benchmark integration in the evaluation framework for lmms-eval, with targeted data-download optimizations, new YAML configs, and supportive utilities to enable streamlined, reproducible benchmarking. This work enhances evaluation coverage and reduces data transfer overhead, enabling faster iteration and clearer business value in model evaluation workflows.
1 Commits • 1 Features
May 1, 2026Delivered VideoNet benchmark integration in the evaluation framework for lmms-eval, with targeted data-download optimizations, new YAML configs, and supportive utilities to enable streamlined, reproducible benchmarking. This work enhances evaluation coverage and reduces data transfer overhead, enabling faster iteration and clearer business value in model evaluation workflows.
May 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance100.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
Python programmingconfiguration managementdata processingmachine learning
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