Instructions to use TheStageAI/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheStageAI/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheStageAI/whisper-medium")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheStageAI/whisper-medium", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a3a9d3011e211e9fabd07ad8cbbe56b844e33459d22eba359d34ee18918a473
- Size of remote file:
- 986 MB
- SHA256:
- 5b66140597a098ddf0c6938d6bfc69f27a02aa8c1121b1b17f6c52a217331f37
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.