Instructions to use naleraphael/rasr_base_zhtw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naleraphael/rasr_base_zhtw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="naleraphael/rasr_base_zhtw")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("naleraphael/rasr_base_zhtw") model = AutoModelForCTC.from_pretrained("naleraphael/rasr_base_zhtw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90cd87db27ba66539d7e281f6d636063d3ab3c5f7d0c0e1ba9579e02c18a8233
- Size of remote file:
- 2.99 kB
- SHA256:
- 36a9163393fb6b85ab9754dc500a8171106095c789cc5d76758339e8671f5b54
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.