Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Afrikaans
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use M2LabOrg/whisper-small-af with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M2LabOrg/whisper-small-af with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="M2LabOrg/whisper-small-af", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("M2LabOrg/whisper-small-af") model = AutoModelForSpeechSeq2Seq.from_pretrained("M2LabOrg/whisper-small-af", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4246be6444acd7a69ef1a3071473f8afbc31b8e1779d3cc471c0a8c6826f5f3
- Size of remote file:
- 967 MB
- SHA256:
- 238db4299604d72b7c62cfbad2ad3bbadc5181f87b2a901265bdad518a2bc9a1
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