Instructions to use seastar105/whisper-tiny-komixv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seastar105/whisper-tiny-komixv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seastar105/whisper-tiny-komixv2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seastar105/whisper-tiny-komixv2") model = AutoModelForSpeechSeq2Seq.from_pretrained("seastar105/whisper-tiny-komixv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3c7085805d45eb6eb96bdf56aad3d71ccc7cc8d3e30ce5b18af358a4e0aecd1
- Size of remote file:
- 151 MB
- SHA256:
- 6880db6b7256be684769ae535f88e8b744dad868093a5edc688b07cf93fa95e7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.