Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use shalanova/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shalanova/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shalanova/whisper-tiny-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shalanova/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("shalanova/whisper-tiny-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e22718eeddfb9ee8f1ad47f1838fe5feab39455460e00521802b5aa014a79159
- Size of remote file:
- 5.5 kB
- SHA256:
- 2283d55dec7be2a6fdba9e3a9219348fb0eb8f47c7f849915c311b5d08ec0a85
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