Instructions to use ouob/whisper-base-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ouob/whisper-base-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ouob/whisper-base-hi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ouob/whisper-base-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("ouob/whisper-base-hi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd7480de55b21097af69106028a18066bd6a647eeeebd95dec3c88479879fa51
- Size of remote file:
- 4.16 kB
- SHA256:
- a0c13dcb45158bcd3c5209a2682e098a436c80a90da4563b54671811d773f268
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