Sync model repo (text/metadata)

README.md

@@ -179,6 +179,7 @@ This model is intended for developers evaluating automatic speech recognition wo
 Quantization keeps a small set of layers in FP32 to preserve accuracy: proj_out/lm_head, the encoder and decoder positional embeddings, and encoder.conv1/encoder.conv2. Audio inputs are limited to 30 seconds (3000 mel time frames) per chunk; longer audio must be chunked externally before inference.
 
 `example.py` forces English transcription by hardcoding the decoder prefix to `<|en|>, <|transcribe|>, <|notimestamps|>`. This is an example-level default, not a model restriction: the bundled tokenizer and decoder support the full multilingual Whisper vocabulary (98 language tokens) and the `<|translate|>` task, so other languages or the translate task can be enabled by changing the forced-prefix token IDs in `example.py`, with no re-export required.
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 - Sample input: `sample_input.flac` is utterance `5338-24615-0014` of the [LibriSpeech ASR corpus](https://www.openslr.org/12) (dev-clean split) by Panayotov et al., via OpenSLR ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)).
 
 ## About this version