Sync model repo (text/metadata)
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benchmarks/README.md
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# Benchmarks
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Machine-readable measurement records for this model, conforming to
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-
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v1.0.0 (`task: vision-classification`).
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These complement — they don't replace — the eval block in the model
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## Provenance
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Source:
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(`report.json`, `metadata.yaml` / `metadata_raspberry.yaml`,
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`huggingface/README.md`). The records map from `report.json` (real Pi 5
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hardware run); the FP32 baseline is reconstructed from its `original`
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# Benchmarks
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Machine-readable measurement records for this model, conforming to
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the AI Portal model schema
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v1.0.0 (`task: vision-classification`).
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These complement — they don't replace — the eval block in the model
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## Provenance
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Source: the delivery package `swin_tiny_raspberry_executorch.zip`
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(`report.json`, `metadata.yaml` / `metadata_raspberry.yaml`,
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`huggingface/README.md`). The records map from `report.json` (real Pi 5
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hardware run); the FP32 baseline is reconstructed from its `original`
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benchmarks/swin-tiny-raspberrypi5-fp32.yaml
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# Pairs with `swin-tiny-raspberrypi5-int8.yaml` to demonstrate the
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# baseline-comparison join.
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#
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# Source:
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# `report.json` `original` fields (the un-quantised baseline measured under
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# identical target / runtime / dataset / benchmark conditions to the optimised
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# record).
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# Same target / runtime / dataset / benchmark as the INT8 record — the
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# disambiguator is `weight_dtype` (and, once published, `model.id`).
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#
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# Hand-curated rather than redelivered:
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# optimised metadata.yaml, so this baseline is reconstructed from report.json.
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#
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# Note: the delivery's vendored huggingface/metadata.yaml is the *Emulation*
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# Pairs with `swin-tiny-raspberrypi5-int8.yaml` to demonstrate the
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# baseline-comparison join.
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#
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# Source: the producer delivery package `swin_tiny_raspberry_executorch.zip`,
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# `report.json` `original` fields (the un-quantised baseline measured under
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# identical target / runtime / dataset / benchmark conditions to the optimised
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# record).
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# Same target / runtime / dataset / benchmark as the INT8 record — the
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# disambiguator is `weight_dtype` (and, once published, `model.id`).
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#
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# Hand-curated rather than redelivered: the producer's pipeline only emits the
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# optimised metadata.yaml, so this baseline is reconstructed from report.json.
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#
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# Note: the delivery's vendored huggingface/metadata.yaml is the *Emulation*
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