Instructions to use bh4/whisper-ben with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bh4/whisper-ben with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bh4/whisper-ben")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bh4/whisper-ben") model = AutoModelForSpeechSeq2Seq.from_pretrained("bh4/whisper-ben") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c56178e4877da9a8ad8a0ff2c6ead5dc8fbac36159c4b2ce318ccab7beeef7d
- Size of remote file:
- 4.8 kB
- SHA256:
- 0332cce835dad802796d7aee3c215688cada43f26ef43e7d80719f4036f8e9fa
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