README.md

---
license: apache-2.0
language:
- ms
- en
base_model:
- mesolitica/malaysian-whisper-base
library_name: mlx
tags:
- whisper
- mlx
- Automatic Speech Recognition
pipeline_tag: automatic-speech-recognition
---

## Malaysian-Whisper-Tiny (MLX)

Apple MLX-converted weights for `PishangShedappp/malaysian-whisper-base-mlx ` optimized for Apple Silicon.

- Base model: `mesolitica/malaysian-whisper-base`
- Format: MLX (`weights.safetensors`, `config.json`)
- Intended runtime: `mlx-whisper` on Apple Silicon (M-series)

### Usage (Python)
```python
import mlx_whisper
result = mlx_whisper.transcribe(
    "/path/to/audio.wav",
    path_or_hf_repo="<this-repo>",
    # Optional decoding controls
    language="ms",               # Malay
    task="transcribe",           # or "translate"
    temperature=0.0,
    no_speech_threshold=0.3,
    logprob_threshold=-1.0,
    compression_ratio_threshold=2.4,
)
print(result["text"]) 
```

### Local HTTP server (FastAPI)
With the server at `whisper/server_mlx.py` from `avatar-npm`:
```bash
export WHISPER_MODEL=<this-repo-or-local-mlx-path>
export WHISPER_LANGUAGE=ml
python server_mlx.py
# POST /transcribe with form field `file`
```

### Notes
- This repo contains only the MLX weights and config. Tokenization and audio
  preprocessing are handled by `mlx-whisper`.
- If you need the original (non-MLX) model, see `mesolitica/malaysian-whisper-base`.

### License
The original model’s license applies. See the upstream repository for details.

### Maintainers
- PishangShedappp