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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a59c45ea7825a4f9c8bbe37629b3e93f8df9c31f7ff1269f1810c5f5974b010
- Size of remote file:
- 967 MB
- SHA256:
- 514982740771812b294b8b9120b263d9a78183192f80a1c10b2766a9a36c3351
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