
Riddhi Bhagwat enhanced the huggingface/feel repository by consolidating the evaluation pipeline and improving data and model integration using Python and YAML. She refactored data loading to leverage load_dataset, updated model and API usage to support Gemma 3, and streamlined reward evaluation for more reliable results. Riddhi expanded multilingual capabilities by adding Hindi support and introduced intuitive UI elements for language management, improving accessibility for end users. Her work also included environment configuration updates and code cleanup, such as standardizing setup with a new environment YAML and clarifying documentation, resulting in a more maintainable and contributor-friendly development workflow.

March 2025 (huggingface/feel) focused on delivering measurable improvements to the evaluation workflow, expanding multilingual capabilities, and standardizing the development environment. The work delivered is aligned with business goals: faster and more reliable evaluation, broader language coverage for end users, and streamlined onboarding for new contributors.
March 2025 (huggingface/feel) focused on delivering measurable improvements to the evaluation workflow, expanding multilingual capabilities, and standardizing the development environment. The work delivered is aligned with business goals: faster and more reliable evaluation, broader language coverage for end users, and streamlined onboarding for new contributors.
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