Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use taohoang/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taohoang/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="taohoang/whisper-tiny-en-US")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("taohoang/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("taohoang/whisper-tiny-en-US", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 905abef27ca509f821a75574a9f34134e0ab9c6e0aff601e7d34af6d34b33e77
- Size of remote file:
- 151 MB
- SHA256:
- c7f022c36b0e4229f5d19d579649d7541198daa7ce1ef734b80b12096364fafe
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