Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use juancopi81/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juancopi81/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="juancopi81/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("juancopi81/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("juancopi81/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15a251d4132c22282a23f3085ca8d7090f1571c552a7dc363f7286725aaa240d
- Size of remote file:
- 151 MB
- SHA256:
- f37a47d8c55d95322f18a5fcf37adc59b200502766ddaf2f7d48c3f83c87a05a
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