Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use CodingQueen13/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodingQueen13/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="CodingQueen13/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("CodingQueen13/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("CodingQueen13/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca7ae66a736c860e89bb782542766bef49e7ad7d7ef6db39b13a1c43379c4619
- Size of remote file:
- 151 MB
- SHA256:
- e6e7d83372e7b5503e856f1fb9717c871526e18222cd129e0717c69fbf2275a8
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