Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Frorozcol/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Frorozcol/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Frorozcol/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Frorozcol/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("Frorozcol/whisper-small-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e192379d991177c11a9c9ace8f56104f36f34b4405d43ce5befae07cb57d687
- Size of remote file:
- 151 MB
- SHA256:
- 0dc4c371838f5fb1b4238a8dc7b075840555637a6f89ff82e920239e85032cd0
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