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README.md
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@@ -29,6 +29,12 @@ All variants take and return fp32 tensors — swap the `.pte` file, keep your ap
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\*Mac arm64, single process, median of 10 — a reference point for relative cost
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only, not a device number (torch eager fp32 on the same machine: 50.8 ms).
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## Verification (executorch 1.4.0, torch 2.13.0)
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Parity is measured against the fp32 eager model on real image input; `corr` is
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\*Mac arm64, single process, median of 10 — a reference point for relative cost
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only, not a device number (torch eager fp32 on the same machine: 50.8 ms).
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### Checked in the task's own units
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Correlation is a first filter. These are the numbers that decide:
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- **int8 (dynamic)** — measured in the units that matter for this model — cosine similarity of the embeddings: median 0.9986 over 10 real images, worst 0.9965.
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## Verification (executorch 1.4.0, torch 2.13.0)
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Parity is measured against the fp32 eager model on real image input; `corr` is
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