Instructions to use tsobolev/whisper-tiny-ka-finetune-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tsobolev/whisper-tiny-ka-finetune-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tsobolev/whisper-tiny-ka-finetune-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tsobolev/whisper-tiny-ka-finetune-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("tsobolev/whisper-tiny-ka-finetune-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d13d465c8ded3b84027f0f70577e6a7024c4c0e6221f41aa1eff65c04c4fce13
- Size of remote file:
- 151 MB
- SHA256:
- cc773dbcf478030160a561dc12b462859512ce75dd060b53b0c541d892c0a761
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