Instructions to use guynich/distil-whisper-large-v2-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guynich/distil-whisper-large-v2-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="guynich/distil-whisper-large-v2-hi")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("guynich/distil-whisper-large-v2-hi") model = AutoModelForMultimodalLM.from_pretrained("guynich/distil-whisper-large-v2-hi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36dedb9487401b05ffce3770d8e62ba2221ddd7bc295f4642c366b4ccb87025c
- Size of remote file:
- 88 Bytes
- SHA256:
- 72e45498923fc12f48912315caf25a45a1bd82843374d066216cc8cb0f806e5a
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