Instructions to use Isaacyn/whisper-small-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isaacyn/whisper-small-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Isaacyn/whisper-small-id")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Isaacyn/whisper-small-id") model = AutoModelForSpeechSeq2Seq.from_pretrained("Isaacyn/whisper-small-id") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d5dcfa776e4903bea965f2b9142cf77aa6864f61bd0ba8a0dd82a6c127217857
- Size of remote file:
- 353 MB
- SHA256:
- 50b3082c4078e3edf90e8ceca2d549de42b9aa6e9c3e6c81589be64562633056
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.