Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use jason1i/whisper-tiny-minds14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jason1i/whisper-tiny-minds14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jason1i/whisper-tiny-minds14")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("jason1i/whisper-tiny-minds14") model = AutoModelForSpeechSeq2Seq.from_pretrained("jason1i/whisper-tiny-minds14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf2df18ebd15f2f370a67448d5b68e0548c37b800b4c3d9a99bca2e5a61c0e1a
- Size of remote file:
- 151 MB
- SHA256:
- 06796f5847ba0c8eaf33934d3f9135b483b2836d795c9d0468d0aeaa5ef57176
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