Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use shtif/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shtif/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shtif/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shtif/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("shtif/whisper-tiny-en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4c0ad5987ef9c57063de708763d1cab81a61e24997124ee9015efd94995e176
- Size of remote file:
- 3.77 kB
- SHA256:
- 37bac0aeabdd29f819b0d73118ea3e58b1b0dc1c4c844fc2837ee01a4380d8dc
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