Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Swedish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-sv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-sv") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-sv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b2d4b265fc9f7dc6e610744a9eb87ff07d16bc51aebaf1af223fdfc404fec3f
- Size of remote file:
- 5.24 kB
- SHA256:
- f3d61310cf9ee56d1fe1ed4fb06013a54464eb10d9db26c430d9447e65a88433
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