Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Swahili
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use pplantinga/whisper-small-sw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pplantinga/whisper-small-sw with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pplantinga/whisper-small-sw")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("pplantinga/whisper-small-sw") model = AutoModelForSpeechSeq2Seq.from_pretrained("pplantinga/whisper-small-sw", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Add base_model information to model (#2)
- Librarian Bot: Add base_model information to model (8d56ef20abdaae9e829efa32b5430b5b2e69e8bb) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>94043bb
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (6c1c095715c5c56db624f414b44156332e7e1868) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>4a767e7
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update model card README.md
6767737 -
End of training
cebd1e7 -
update model card README.md
4160ff8 -
Model save
153f306 -
initial commit
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