Instructions to use CheeLi03/whisper-tiny-five with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CheeLi03/whisper-tiny-five with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CheeLi03/whisper-tiny-five", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c27365909f77be0ee863fbbca8e1fd4360e1dc5469b40598fe4e71ef3f45667
- Size of remote file:
- 2.38 MB
- SHA256:
- 4895ef485a07cf3fd06008b53c8a836f04ae7cfd0b63f8b0f24436acd8de17b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.