Instructions to use yip-i/colab-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yip-i/colab-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yip-i/colab-demo")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("yip-i/colab-demo") model = AutoModelForCTC.from_pretrained("yip-i/colab-demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ea5b9a9d6fa1c2fb01872daa62f4ed2f53893850b0dd596f7627da7a975e02
- Size of remote file:
- 3.38 kB
- SHA256:
- c5c9bb51ce50ebb4d7e3550c506003f0041454a6a1f159d79db45d5c9650cf44
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.