Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use GCYY/whisper-tiny-asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GCYY/whisper-tiny-asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GCYY/whisper-tiny-asr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("GCYY/whisper-tiny-asr") model = AutoModelForSpeechSeq2Seq.from_pretrained("GCYY/whisper-tiny-asr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5172407b0356e098ecc1c9a701e2111f2a5e46d73daddc574a33dbf9d0cec97f
- Size of remote file:
- 4.16 kB
- SHA256:
- 877cd78395aef6442599c80aac61f0dec6cc1bc56f0c8c47aaf4d6d78f66e78f
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