Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use beltrewilton/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beltrewilton/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="beltrewilton/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("beltrewilton/whisper-small-dv") model = AutoModelForMultimodalLM.from_pretrained("beltrewilton/whisper-small-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- becd9b89a6fee7d917b255562cdb2793096a09ca9f21f42cb86ac12261ee0a8e
- Size of remote file:
- 4.73 kB
- SHA256:
- 6599cbca286e01f4fa12f0a0fc4f27ee5bb6db8cc469edcb6136d9f02108ee25
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