Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use preetam8/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use preetam8/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="preetam8/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("preetam8/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("preetam8/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6c6252c7a03a56f5c8d61d79454e2d920d887a15e0ce29385c90996879d6d0e
- Size of remote file:
- 5.3 kB
- SHA256:
- 3a6eca145db14619abf139c2995194a441e798e92b999f2edeeddecb34da0db5
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