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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.
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