Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use bayerasif/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bayerasif/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bayerasif/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bayerasif/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("bayerasif/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 930935a91967edbdda3fd67015ed7c9329ac208115f2c72889435b26ae23f869
- Size of remote file:
- 4.66 kB
- SHA256:
- 60e50cdd483301d78314aa015ebb6a930d9a94e16b25f78f1e5b0cd987e5cf78
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