Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use crcdng/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crcdng/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="crcdng/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("crcdng/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("crcdng/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33ee9a49f775e73d7a9977a695996d824666c3909d122bf935926f959dbb19d0
- Size of remote file:
- 151 MB
- SHA256:
- 93a7f6f7dde725c38e059d9c4a6c259a8da2d0308467dfb4046905b15a69f818
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