ZippriZIPPRIAI HUB · RABBIT INDUSTRIES
AI Hub / Model & Dataset Hub
MODELS · DATASETS · SEARCH · DATA STUDIO

Discover AI assets with the evidence and metadata attached.

Zippri AI Hub combines model and dataset discovery with structured cards, repository versions, signed provenance, trust signals and permission-aware Dataset Studio previews. Search can filter by AI type, task, language, license, verification, gated access and explicitly declared native-from-scratch status.

AI model hubdataset studiomodel cardsdataset viewerAI model searchgated datasets
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Public before loginCore information is readable without an account.
Evidence-awareProduct claims follow current verified platform state.
Human authorityHigh-risk actions remain explicitly approval-gated.
End-to-end AI lifecycleBuild, verify, benchmark, deploy and commercialize.

Model Card 2.0

Model repositories can publish structured task, architecture, parameter count, context length, language, modality, runtime, base-model, training-type, intended-use and limitation metadata without replacing immutable Git/CAS evidence.

Structured Models

Model Card 2.0 metadata beside signed provenance, benchmarks and versions.

Data Studio

Permission-aware dataset inspection without automatically downloading the full artifact.

AI Search

Find relevant assets by metadata and trust state, not only by repository name.

Gated Assets

Manual or domain-policy approval before protected asset access.

Dataset Studio

CSV, TSV, JSON, JSONL and text artifacts can expose bounded row previews, columns and sample statistics. Parquet assets expose semantic metadata and partial-checkout intelligence; row preview is only enabled when a dedicated supported reader is available.

Universal AI search

Search combines repositories and lifecycle objects and adds AI-specific filters including task, language, license, verification, gated status and explicit native-from-scratch declarations.

Gated access

Public discovery can remain visible while Cards, Dataset Studio and artifact downloads require an approved access request. Existing organization ownership and commercial license rights remain authoritative.

Common questions about Model & Dataset Hub

Is a gated repository completely hidden?

No. Discovery metadata can remain visible while protected Card, dataset and artifact access requires approval.

Does Dataset Studio download an entire dataset?

No. Preview is bounded. Large-format partial checkout uses the existing semantic storage layer where supported.

Does native-from-scratch search infer ancestry automatically?

No. The filter only matches an explicit declaration in structured metadata; provenance and verification remain separate evidence layers.

Related AI Hub topics

AI DatasetsManage AI datasets, corpus revisions, metadata, storage, provenance and downstream impact alongside the models and training runs that use them.AI Model RepositoryVersion AI source, models, checkpoints and datasets with real Git plus encrypted content-addressed storage, semantic artifact indexing and signed repository history.AI ProvenanceBuild signed AI provenance graphs linking repositories, revisions, Git, CAS, datasets, environments, checkpoints, benchmarks, verification and releases.AI VerificationVerify AI artifacts against current evidence, issue signed verification receipts and govern Trust Passports without converting self-claims into approval.Native AI DevelopmentPlan and govern native AI or foundation-model development from corpus and tokenizer work through checkpoints, provenance, evaluation, release and deployment.
Zippri separates engineering readiness from external/provider acceptance. Public pages preserve REVIEW and external-gate states instead of presenting unfinished external integrations as live.