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")# 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
- Xet hash:
- 3b944c2651198281b5e6ad876b3949b6189cd5b6d96b9597a436518831447678
- Size of remote file:
- 967 MB
- SHA256:
- f49dcdec8282d51ce4040170971d11483cdd5ff832401c6c07e3b71ed5b44647
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