Push metadata and canonical datasets to HuggingFace repositories with gated access.
npx skills add https://github.com/intertwine/security-verifiers --skill sv-hf
Please help me install this Agent Skill. Skill: sv-hf Source: https://github.com/intertwine/security-verifiers/tree/main/skills/sv-hf Command: npx skills add https://github.com/intertwine/security-verifiers --skill sv-hf
This Skill streamlines the process of managing and deploying datasets for the Security Verifiers project on the HuggingFace Hub, ensuring efficient data sharing and access control.
Use the sv-hf skill to push the E1 metadata to the public HuggingFace repository for your organization.
High-intent search queries and answers about installing and using this skill.
You can push HuggingFace datasets with gated access by configuring private repositories during the dataset setup process. This Skill enables gated access configuration to prevent training contamination, ensuring only authorized researchers can download the canonical splits.
Yes, you can validate your dataset schema before pushing to the HuggingFace Hub. This Skill performs dataset validation to ensure schema consistency for canonical splits and metadata, preventing malformed data from being published to your public or private repositories.
The best way to manage HuggingFace dataset repositories for security verifiers is to use this Skill, which integrates directly with the HuggingFace Hub for version control and access management. It handles pushing metadata and canonical splits across E1 and E2 environments.
Yes, this Skill supports pushing both metadata-only and full canonical datasets to HuggingFace repositories. This allows you to publish dataset information without exposing the underlying data until proper access is granted through the Hub's gated access controls.
You set up user datasets for E1 and E2 environments by using this Skill to push the required metadata and canonical splits to the designated public or private HuggingFace repositories. It handles the environment-specific configuration for your organization.
Without gated access, pushing private datasets to HuggingFace risks training contamination and unauthorized access. This Skill mitigates that limitation by enabling gated access configuration on private repositories, ensuring sensitive security verifier data remains restricted to authorized users.
richfremValidate HuggingFace environment variables and create a structured dataset repository on the Hub.
intertwineBuild and validate Security Verifiers E1 and E2 datasets with Pydantic schemas.
zerwizManage Hugging Face Hub repositories, models, datasets, and endpoints via the hf CLI.
skkeoriwManage Hugging Face Hub models and datasets via the hf CLI.
