Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Finnish
whisper
whisper-small
mozilla-foundation/common_voice_11_0
finnish
whisper-event
Instructions to use RASMUS/whisper-small-fi-15k_samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RASMUS/whisper-small-fi-15k_samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RASMUS/whisper-small-fi-15k_samples")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RASMUS/whisper-small-fi-15k_samples") model = AutoModelForSpeechSeq2Seq.from_pretrained("RASMUS/whisper-small-fi-15k_samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7311e7634582e6329b348c217c86047159e48b5601efa30b3a6016351512760d
- Size of remote file:
- 3.58 kB
- SHA256:
- 38939ef7c18a7e4a7a14b4469c8fb2a39c43a9acbdc8b892e37cab0383b8b584
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