Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use TieIncred/whisper-tiny-enUS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TieIncred/whisper-tiny-enUS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TieIncred/whisper-tiny-enUS")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("TieIncred/whisper-tiny-enUS") model = AutoModelForSpeechSeq2Seq.from_pretrained("TieIncred/whisper-tiny-enUS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bc8f686c6d0a6ba9015ceced1e51dc304b917422a9ff1a18ef44261e71b90e9
- Size of remote file:
- 151 MB
- SHA256:
- 6a4b8322daa60036d36f479d23eb5ee563424f939e844bbffc70560c66f16062
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