Sync model repo (text/metadata)

README.md

@@ -1,6 +1,5 @@
 ---
 library_name: executorch
-display_name: DeiT-Tiny INT8 — Ethos-U85 (ExecuTorch)
 license: apache-2.0
 base_model: facebook/deit-tiny-patch16-224
 base_model_relation: quantized

benchmarks/README.md

@@ -1,21 +0,0 @@
-# Benchmarks
-
-Machine-readable measurement records for this model (`vision-classification` schema).
-
-## Files
-
-- `deit-tiny-int8-ethos-u-executorch-alif-dk-e8-int8.yaml` — optimized INT8 measurements on the Alif DK-E8
-  (Cortex-M55 host + Ethos-U85 NPU) via the ExecuTorch `ethos-u` backend.
-- `deit-tiny-int8-ethos-u-executorch-alif-dk-e8-fp32.yaml` — FP32 reference accuracy (PyTorch; the baseline was
-  not compiled to the NPU, so no on-device performance).
-
-## Ethos-U metrics deferred
-
-These are **regular vision-classification** records for now. The delivery also carries
-NPU-specific metrics that the 0.6.0 schema's `additionalProperties: false` rejects —
-target `npu_model`/`npu_num_macs` and performance `sram_peak_bytes`, `flash_footprint_mib`,
-`mac_utilization_pct`, `total_cycles`, `active_cycles`, `effective_cycles_ratio_pct`. They
-are **preserved in `metadata.yaml`** and will be added back to these records once a schema
-holds the embedded-NPU profile (see [`upstream.md`](../../../docs/marvik/upstream.md) and
-[ai-portal-model-schema#4](https://github.com/Arm-Collaboration/ai-portal-model-schema/pull/4)).
-`peak_memory_mb` here is the SRAM working-memory peak (`sram_peak_bytes / 1048576`).

benchmarks/deit-tiny-int8-ethos-u-executorch-alif-dk-e8-fp32.yaml

@@ -1,7 +1,3 @@
-# FP32 baseline measurement record — DeiT-Tiny INT8 reference accuracy.
-# The FP32 baseline was NOT compiled/run on the Ethos-U85 (delivered as a PyTorch
-# reference, performance: null), so this carries reference accuracy only — no on-device
-# latency/memory. runtime/benchmark describe the PyTorch eval on the ImageNet workload.
 version: 1.2.0
 report_type: vision-classification
 profile: Baseline

benchmarks/deit-tiny-int8-ethos-u-executorch-alif-dk-e8-int8.yaml

@@ -1,10 +1,3 @@
-# Optimized measurement record — DeiT-Tiny INT8 on Alif DK-E8 (Ethos-U85 NPU, ExecuTorch).
-# Onboarded as a regular vision-classification model; NPU-specific metrics are omitted
-# here until the schema supports them (docs/marvik/upstream.md + ai-portal-model-schema#4):
-# target npu_model/npu_num_macs and performance sram_peak_bytes, flash_footprint_mib,
-# mac_utilization_pct, total_cycles, active_cycles, effective_cycles_ratio_pct — all
-# retained in metadata.yaml. peak_memory_mb is the SRAM working-memory peak
-# (sram_peak_bytes / 1048576).
 version: 1.2.0
 report_type: vision-classification
 profile: Arm-Optimized