Automatic Speech Recognition
Transformers
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use kul-speech-lab/whisper_small_CGN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kul-speech-lab/whisper_small_CGN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kul-speech-lab/whisper_small_CGN")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kul-speech-lab/whisper_small_CGN") model = AutoModelForSpeechSeq2Seq.from_pretrained("kul-speech-lab/whisper_small_CGN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8104aa5401ee6dcd28e1b3fa42b3761cde1b6e9848df82ff337c583063bf0ba4
- Size of remote file:
- 3.71 kB
- SHA256:
- cffdf600c8675f2764efd8377ebef642224cf40da534680accf9eb16fc05707c
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