Instructions to use razhan/whisper-small-ckb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-small-ckb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-small-ckb")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-small-ckb") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-small-ckb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 849bd6d28884d45f1c6807234c23fe4e7e630466c23da0211ae8a8005a55540a
- Size of remote file:
- 3.58 kB
- SHA256:
- e8353651185f78a30487357bbc2b9492d051cfb8a49fa33462175d71f2478a05
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.