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README.md

@@ -9,29 +9,39 @@ tags:
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 # efficientnet_b1 — ExecuTorch XNNPACK
 
-`efficientnet_b1_xnnpack_fp32.pte` (31.2 MB, fp32, XNNPACK-delegated)
-
 - **Source**: torchvision efficientnet_b1 IMAGENET1K_V2
 - **License**: BSD-3-Clause
 - **Input**: [[1, 3, 240, 240]] — RGB, ImageNet norm, 240x240
 - **Output**: ImageNet logits [1,1000]
 
-## Verification (Mac arm64, executorch 1.4.0, torch 2.13.0)
+## Variants
+
+All variants take and return fp32 tensors — swap the `.pte` file, keep your app code.
+
+| precision | file | size (MB) | parity vs fp32 eager (worst corr) | Mac median (ms)* |
+|-----------|------|-----------|------------------------------------|------------------|
+| fp32 | `efficientnet_b1_xnnpack_fp32.pte` | 31.2 | 1.000000 | 9.3 |
+| fp16 | `efficientnet_b1_xnnpack_fp16.pte` | 28.8 | 0.999816 | 54.9 |
+
+\*Mac arm64, single process, median of 10 — a reference point for relative cost
+only, not a device number (torch eager fp32 on the same machine: 352.7 ms).
+
+### Precisions that did not earn a slot
 
-Parity vs torch fp32 eager on random input:
+- **int8 is not shipped**: worst-output corr 0.077 against fp32 eager, below the 0.95 bar for this precision. The file converts and runs; the numbers do not hold up, so it is left out rather than shipped with a warning.
+
+## Verification (executorch 1.4.0, torch 2.13.0)
+
+Parity is measured against the fp32 eager model on real image input; `corr` is
+the correlation over all elements of each output tensor.
 
 | output | shape | max_abs_diff | corr |
 |--------|-------|--------------|------|
-| 0 | [1, 1000] | 6.676e-06 | 1.000000 |
+| 0 | [1, 1000] | 1.490e-05 | 1.000000 |
 
-Median latency over 10 runs (single Mac process, reference only — device numbers to follow):
-ExecuTorch 9.2 ms vs torch eager 345.4 ms.
+XNNPACK delegate coverage (fp32): 100.0% (410/410 ops)
 
 ## Conversion
 
 torch.export -> to_edge_transform_and_lower(XnnpackPartitioner) -> .pte
 (conversion scripts: [executorch-models](https://github.com/john-rocky/executorch-models))
-
-
----
-Part of [executorch-models](https://github.com/john-rocky/executorch-models) — a verified .pte zoo for ExecuTorch. Conversion scripts and all models are indexed there.