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:
- a075027589351cebd1f5478edf2523c2cae2e122754d331edd43ab490bbdde39
- Size of remote file:
- 290 MB
- SHA256:
- 5d8507a06c6394fbf19eeb381feed3d637688527abae7557951caa9b9df85ac0
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