Automatic Speech Recognition
Transformers
PyTorch
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ruisp/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruisp/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ruisp/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ruisp/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("ruisp/whisper-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 906b2415647a25646cf9243137dfee120195dec36b0fd67466796875703d9f6a
- Size of remote file:
- 4.14 kB
- SHA256:
- fb1fb55f6f5aaaaaa7fa2762408c376669f9d1e0d44d38cb3e3c08af06154125
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