Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use jamesthong/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamesthong/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jamesthong/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jamesthong/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("jamesthong/whisper-small-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f52ae905b57e80a5a41c56488f07def770b9c8a7adbfbe4f2e4b71453239fe48
- Size of remote file:
- 151 MB
- SHA256:
- b7adfcbf5f70bf37d989f53e25048c403c1df5d3e9d0022b403d4a806e41de0d
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