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:
- de370c1f90f632b3314265ed02a8017441199139627d2ed5932a86f0595f1052
- Size of remote file:
- 967 MB
- SHA256:
- 78c11df80c56692a772e9239eb7590092fd5c7dfc02d4491fdbd4fac5e7f3b53
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