| # Local validation — 2 November 2026 |
|
|
| This record covers the supplied Maya Transcribe checkpoint. It does not reproduce the authors’ eight-condition recognition benchmark or A100/vLLM serving measurements. |
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|
| ## Verified |
|
|
| - ZIP extraction completed with CRC checks and per-file SHA256 records. |
| - All eight original non-card model files remain byte-identical to the archive: weights, config, generation config, processor config, tokenizer config, tokenizer, chat template and Git attributes. |
| - Safetensors header: 611 tensors, 782,426,112 stored elements, all BF16; 1,564,928,088 weight-file bytes. |
| - Native AutoProcessor and AutoModelForMultimodalLM load locally with `trust_remote_code=False`; no model/processor code was fetched. |
| - Real model inference passed in native and mixed styles, plus a two-clip batch with distinct prompts. |
| - Seven CLI checks passed: dependency-free help; stereo downmix/resampling; empty, overlong and non-finite audio rejection; existing-output preservation; invalid-style rejection. |
|
|
| ## Environment and audio |
|
|
| macOS Apple Silicon, Python 3.12.14, PyTorch 2.15.0, Transformers 5.20.2, Apple MPS with float32 inference. Original BF16 weight files are unchanged. Dependencies are pinned in requirements.txt. |
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| The smoke input is a 7.76-second, 24 kHz mono **synthetic** Hindi clip generated by Maya 2 Native, Ritvik voice. It was resampled to 16 kHz. Source: https://huggingface.co/maya-research/maya2-native/resolve/main/samples/hi_ritvik.wav . This is a functional example, not a natural-speech evaluation dataset. |
| |
| ## Actual outputs |
| |
| **style: native** |
| |
| क्या आपका वर्तमान पता पैंतालीस एमजी रोड अंधेरी ईस्ट मुंबई चार शून्य शून्य शून्य छः नौ है यदि हाँ तो एक दबाएँ |
| |
| **style: mixed** |
| |
| क्या आपका वर्तमान पता पैंतालीस mg road अंधेरी east मुंबई चार शून्य शून्य शून्य छः नौ है यदि हाँ तो एक दबाएँ |
| |
| Both outputs terminated below the 512-token cap. Reported CLI elapsed times include loading, preprocessing and generation, and were run under different cache/warm-up conditions. They are not a latency comparison or serving benchmark. |
| |
| ## Not verified here |
| |
| - The authors’ WER values, scorer/normalizer implementation, evaluation split independence or comparison significance. |
| - CUDA/A100 inference, vLLM 0.29 serving, production concurrency/latency, or minimum VRAM. |
| - Natural microphone recordings, noisy/phone robustness, English-only quality, diarization, timestamps, real-time streaming or long-form orchestration. |
| |
| ## Reproduce |
| |
| ```bash |
| pip install -r requirements.txt |
| python transcribe.py /path/to/authorized/hindi_clip.wav --style native |
| python transcribe.py /path/to/authorized/hinglish_clip.wav --style mixed |
| ``` |
| |
| These commands run locally. No hosted API calls or GPU instances were provisioned in this preparation. |
| |
