Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Instructions to use BanUrsus/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BanUrsus/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BanUrsus/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BanUrsus/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("BanUrsus/whisper-small-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24c294a8c63d676aa13cfb7d7e17c31834df23745e6b9fa8f2bd23758d090d12
- Size of remote file:
- 4.6 kB
- SHA256:
- 8448fe1f636c8610ae2aace21825f804ea699aec3e07a196d7ca9c29dfaec8f3
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