configs:
- config_name: default
data_files:
- split: train
path: data/repositories.parquet
- config_name: relations
data_files:
- split: train
path: data/relations.parquet
Snapshot status
Repositories: 5645805. Relations: 2296847.
Coverage is complete; see manifest.json for scan details.
hf-ml
hf-ml is a machine learning repository registry built from Hugging Face Hub
metadata. The default configuration contains one row per observed model,
dataset, or Space repository. The relations configuration contains explicit
links between repositories, including derived or fine-tuned artifacts when the
source metadata supports that relationship.
Each snapshot includes a coverage manifest recording repository types, scan windows, pagination, and any incomplete or failed pages. Coverage is therefore measurable and auditable; this initial dataset does not claim exhaustive Hub coverage. The registry stores metadata and relationships only. It does not copy model weights, dataset payloads, or Space artifacts.
Relationship semantics
For lineage relationships named finetune, adapter, merge, quantized, or
base_model, source_key identifies the child or derived model and
target_key identifies its parent or base model. A generic base_model
relationship is used when the metadata declares a base model but does not make
the more specific relationship type explicit. target_exists: false means the
referenced repository was not present in that snapshot; it does not invalidate
the relationship declaration.
Repository metadata and README content remain attributable to their original Hub authors. See the manifest for the snapshot timestamp, source queries, and file checksums.