Sync model repo (text/metadata)

README.md

@@ -19,7 +19,7 @@ Whisper Small, an encoder-decoder Transformer for automatic speech recognition,
 
 This repository contains an Arm-optimized version of openai/whisper-small for automatic speech recognition. The model is provided in ExecuTorch (`.pte`) format, targeting Premium Smartphone systems.
 
-This version is intended to demonstrate efficient inference on Arm-based platforms while preserving the original model's intended behavior. Arm has evaluated this model on LibriSpeech ASR and measured performance on Vivo X300.
+This version is intended to demonstrate efficient inference on Arm-based platforms while preserving the original model's intended behavior. Arm has evaluated this model on LibriSpeech ASR and measured performance on vivo X300.
 
 **Key results**
 
@@ -27,7 +27,7 @@ This version is intended to demonstrate efficient inference on Arm-based platfor
 |---|---|
 | Model format | ExecuTorch (`.pte`) |
 | Target device class | Premium Smartphone |
-| Reference device | Vivo X300 (C1-Ultra, C1-Premium, C1-Pro; Android 16 / OriginOS 6) |
+| Reference device | vivo X300 (C1-Ultra, C1-Premium, C1-Pro; Android 16 / OriginOS 6) |
 | Primary performance result | 7802.5 ms p50 latency, RTFx 0.90 |
 | Accuracy result | Normalised WER 3.41%, CER 1.29% |
 | Size / memory result | 395.05 MB, 2.72 x smaller than the baseline (1074.76 MB) |
@@ -66,7 +66,7 @@ Performance was measured on the reference configuration below. Results are inten
 
 | Field | Value |
 |---|---|
-| Device / platform | Vivo X300 |
+| Device / platform | vivo X300 |
 | CPU / accelerator | C1-Ultra, C1-Premium, C1-Pro (aarch64, 8 cores), CPU execution backend |
 | OS | Android 16 / OriginOS 6 |
 | Runtime | ExecuTorch 1.1.0 |

pyproject.toml

@@ -13,7 +13,7 @@ dependencies = [
 
 [tool.uv]
 package = false
-# The example runs on Arm-based Linux; ExecuTorch and its Vivo X300 export target
+# The example runs on Arm-based Linux; ExecuTorch and its vivo X300 export target
 # aarch64. Restricting the resolution environment keeps the lock to the wheels
 # that platform actually installs.
 environments = ["sys_platform == 'linux' and platform_machine == 'aarch64'"]