Instructions to use mobilint/whisper.cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/whisper.cpp with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="whisper.cpp", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
File size: 2,232 Bytes
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license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper
- automatic-speech-recognition
- ggml
- mobilint
- npu
language:
- en
- zh
- de
- es
- ru
- ko
- fr
- ja
- pt
- tr
- pl
- multilingual
library_name: whisper.cpp
---
# whisper.cpp Models for Mobilint NPU
This repository provides all model files needed to run [whisper.cpp-mblt](https://git.mobilint.com/algorithm-team/integration/whisper.cpp-mblt), the Mobilint NPU-accelerated fork of [whisper.cpp](https://github.com/ggml-org/whisper.cpp).
## Available Files
| Model | File | Size | Description |
|-------|------|------|-------------|
| whisper-small | `ggml-small.bin` | 466 MB | GGML model (tokenizer + weights for CPU fallback) |
| whisper-small | `ggml-small-encoder.mxq` | 93 MB | Mobilint NPU encoder |
| whisper-small | `ggml-small-decoder.mxq` | 159 MB | Mobilint NPU decoder |
## Usage
### NPU Inference (Mobilint)
```bash
# Download all files and run
whisper-cli-mblt \
-m ggml-small.bin \
--mxq-encoder ggml-small-encoder.mxq \
--mxq-decoder ggml-small-decoder.mxq \
-f audio.wav
# Or auto-download from HuggingFace
whisper-cli-mblt -hf mobilint/whisper-small -f audio.wav
```
### CPU Inference (standard whisper.cpp)
The `ggml-small.bin` file is also compatible with standard whisper.cpp for CPU-only inference:
```bash
whisper-cli -m ggml-small.bin -f audio.wav
```
## Model Details
- **Base model**: [openai/whisper-small](https://huggingface.co/openai/whisper-small) (244M parameters)
- **Languages**: 99 languages supported (English, Chinese, German, Spanish, Russian, Korean, French, Japanese, Portuguese, Turkish, Polish, and more)
- **Tasks**: Transcription and translation (to English)
- **NPU pipeline**: Audio → mel spectrogram (CPU) → encoder (NPU, global4) → decoder (NPU, single core, greedy) → text
## Related Repositories
- **[mobilint/whisper-small](https://huggingface.co/mobilint/whisper-small)** — Original Mobilint whisper-small model with config.json and tokenizer files
- **[ggerganov/whisper.cpp](https://huggingface.co/ggerganov/whisper.cpp)** — Upstream GGML models for CPU inference
## License
Apache 2.0 (same as the original OpenAI Whisper model)
|