Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Luo (Kenya and Tanzania)
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Clement33/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Clement33/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Clement33/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Clement33/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("Clement33/whisper-small-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1893ff47af1449ba8ea04f53b9a6004d3e1a2ca58353483f66ce77a3a0dce4ad
- Size of remote file:
- 5.33 kB
- SHA256:
- 6b3c5b9e73b574f5e0f8b651f8d2a6979284cf0ad0bcd31db7c7cbe3eac2956e
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