niznik-dev

Generates interactive visualizations from experiment evaluations using inspect-viz, enhancing data analysis and reporting.

Assists in planning LLM fine-tuning and evaluation experiments, guiding users through a structured YAML configuration process.

Automates the setup of experimental infrastructure for machine learning, orchestrating fine-tuning and evaluation configurations efficiently.

Facilitates the orchestration of machine learning experiments, ensuring model optimization and evaluation are executed sequentially.

Summarizes experiment results by extracting key metrics like training loss and accuracy from completed experiments.

Converts experiment analysis reports from markdown to PDF using pandoc, ensuring shareable and well-formatted documents.

Guides users in creating custom evaluation tasks for inspect-ai through an interactive workflow, ensuring best practices and documentation.

Facilitates the creation of weekly software meeting agendas by automating the process of copying and updating previous agendas in a wiki repository.