Automatic Speech Recognition
Transformers
PyTorch
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Runningpony/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Runningpony/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Runningpony/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Runningpony/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("Runningpony/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe5c1de24b102f739f82e0efb150e8f3565e53eed86a42c6e9f073de8cdd0140
- Size of remote file:
- 967 MB
- SHA256:
- 51b48f79288d1934dc0c012caac631055940d8fea62f47fc120a482a9785412a
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