Instructions to use hyperion-shuo/whisper-small-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyperion-shuo/whisper-small-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hyperion-shuo/whisper-small-zh")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hyperion-shuo/whisper-small-zh") model = AutoModelForSpeechSeq2Seq.from_pretrained("hyperion-shuo/whisper-small-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12b6e5c423362327f707a242add71a7cd750e478780dc4d93968f85dfc23c41f
- Size of remote file:
- 967 MB
- SHA256:
- d24dbe16cbdbe6812127c1ddacf4f2ebd072ee4c4394a0b8244b08ff69cfb8ac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.