Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Froptor/whisper-small-hi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Froptor/whisper-small-hi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Froptor/whisper-small-hi")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Froptor/whisper-small-hi") model = AutoModelForSpeechSeq2Seq.from_pretrained("Froptor/whisper-small-hi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c5696873394c9edd2c518ff92586a753b43d60d3c3758dccbc51b549ec91597
- Size of remote file:
- 4.73 kB
- SHA256:
- 4effafcdecb587514c95090205044d5eed842fec6466ade57593e3ff3f82888f
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