from skillattack30
Extract, import, and add structured model evaluation results to Hugging Face model cards; run or import benchmark evaluations and generate model-index YAML for
This skill adds a full workflow for extracting benchmark tables from README files, importing benchmark scores from external services (Artificial Analysis), and running custom evaluations locally or on Hugging Face Jobs. It produces model-index YAML entries and can create pull requests to update model cards, with validation and checks to avoid duplicate PRs. It supports lighteval/inspect-ai and vLLM backends for GPU-accelerated evaluations.
Use this skill when you need to add or update evaluation results for a Hugging Face model card: extracting existing tables from README, importing authoritative benchmark scores, or running reproducible evaluation jobs and submitting the results as a PR. It is especially useful for maintainers or contributors who regularly update model-index metadata.
Likely used by agents that can run shell/CLI commands and manage GitHub PRs (Copilot/Code assistant, CLI-capable agents).
This skill has not been reviewed by our automated audit pipeline yet.
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