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
- Xet hash:
- 31a6fd7469f74a5e3c06e6fd113f8e832f1f1eebfa0c75345bf45d97096cadcf
- Size of remote file:
- 488 MB
- SHA256:
- 1be3a9b2063867b937e64e2ec7483364a79917e157fa98c5d94b5c1fffea987b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.