Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use DahmL/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DahmL/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DahmL/whisper-small-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DahmL/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("DahmL/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (a3a7fcd46499b359a429d8a1d03c5d6878acfbb8) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5fef00e
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End of training
4c1d7ba -
initial commit
5598f6d