Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
German
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use alphaply/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alphaply/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="alphaply/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("alphaply/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("alphaply/whisper-small-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d32daf183501c514da0686706cbd3c0711ebf32a2de08b1a861b29ff1634bd34
- Size of remote file:
- 5.91 kB
- SHA256:
- 1b2f8d48440bd0b8749b0d912c41dc351afe7e19e4fd8f2420102c73aa0d5ee9
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