Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use menevsem/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use menevsem/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="menevsem/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("menevsem/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("menevsem/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47d4bb2c0e47921e3d310598bdd6f757aeb05bdc93addcd5487a0eb32382e7f8
- Size of remote file:
- 4.16 kB
- SHA256:
- 5fc116296997ba938bf51596991347955d4e91eaca5f0205e30bb033728d05dc
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