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42 lines
1.7 KiB
Markdown
42 lines
1.7 KiB
Markdown
# Hugging Face Provider And Registry Shape
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Last updated: dev@e57f60b | 2026-07-20
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## Scope
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Canonical placeholder vendor ID `huggingface`; download/fit metadata in
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`services/hwfit/`; OpenAI-compatible inference providers/TGI handled as their
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serving dialect. There is no dedicated Hugging Face canonical reader on
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current `dev`.
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## Hub Model Shape
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Hub model info can provide `modelId`/`id`, `pipeline_tag`, `tags`, `config`, and
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card metadata. Current canonical normalization does not map `pipeline_tag`,
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`config.model_type`, or Hub task/modality fields. An explicitly selected
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Hugging Face vendor uses generic identity-only normalization.
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This source is `cookbook_hf`/registry confidence, not live endpoint truth.
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Free-form tags, README/card prose, repository names, and architecture names do
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not automatically claim capability. A serving engine can load a model with
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missing projection, different template, or disabled parser.
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## Serving Shape
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Hugging Face routed inference and TGI can expose OpenAI-compatible endpoints;
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their model list may be identity-only. Keep Hub identity separate from the
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serving endpoint and merge only when exact revision/model identity is known.
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## Fallback And Safety
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Hub metadata can fill a scoped registry record after provider payload fields
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and probes, but must not overwrite fresh endpoint-negative evidence. Treat
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remote code, model cards, and repository files as untrusted content.
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## Current Gaps
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- Revision/digest linkage between downloads, Hub records, and serving
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endpoints is incomplete.
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- Hub task/family metadata is not consumed by the canonical reader package.
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- Pipeline tags can be missing or overly broad; unknown stays unknown.
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